My Whole Syllabus

SCHEME AND CURRICULUM BOOK
BACHELOR OF TECHNOLOGY
in
Computer Science and Engineering
(Cyber Security)
UG DEGREE 4 YEAR PROGRAMME
Engineering and Technology
(w.e.f. Session 2022-2023)
DEPARTMENT OF COMPUTER SCIENCE AND ENGINEERING

Gurugram University, Gurugram, Haryana
Preface
The overall well-being of a nation depends on the eminence of its human resource. Providing quality
education plays a vital role in transforming people into valuable human resource. Well educated students of
today will become innovators and leaders of tomorrow who are going to ensure a constructively competitive
but sustainable and peaceful world for everyone. Keeping in the view the demand of the skills based on
Cyber Security, the university has introduced a Bachelor of Technology Programme in Computer Science
& Engineering (Cyber Security) in the Department of Computer Science & Engineering. We have designed
the curriculum for B.Tech. Computer Science & Engineering (Cyber Security). The curriculum is designed
around the framework of Outcome-Based Education (OBE) in which students are at the centre of teaching
learning process. The salient features of the curriculum design are as follows:
1. To start with, four Programme Educational Outcomes are defined.
2. The twelve Programme Outcomes (POs) are taken from the Self Appraisal Report format of National
Board of Accreditation (NBA) for undergraduate engineering programmes and two Programme Specific
Outcomes (PSOs) are outlined to capture the specialisations of the B. Tech. CSE (Cyber Security)
programme.
3. An induction programme of three weeks duration has been introduced to make the admitted students
comfortable in their new environment. The induction programme continues in the form of participation in
Sports club or Green club or Cultural, Literature and Film Club etc. for the remaining period of the
programme. It is mandatory for every student to join in one of these clubs.
4. In addition to the professional core and elective courses, there is a provision for many courses from Basic
Sciences, Engineering Sciences, Mathematics and Humanities. The non-credit mandatory courses are
included to make students aware about constitution of India, issues related to environmental and sustainable
development, and Indian traditional wisdom.
5. For every course, 4 to 6 Course Outcomes (COs) are defined which are concrete and measurable.
6. Guidelines for preparing sessional examination question papers and assignments have been framed for
measuring the attainment levels of COs.
7. The internal and external evaluation criteria for various courses has been succinctly described.
8. The Course Outcomes (COs) are mapped to Programme Outcomes (POs) by defining a CO:PO
articulation matrix for every course.
9. The methodology for computing the attainment levels for the Course Outcomes and Programme
Outcomes is laid out.
10. The new curriculum has a focus on the problem solving and learning capabilities of the students. There
are many laboratory courses which give students a hands-on experience in problem solving. Further,
provisions for industry internship/training and project works make students ready to accept challenges and
do research to solve difficult engineering problems.
11. Overall, the curriculum is made keeping in the view the continuous cycle of improvement in teaching
learning process.
Contents
Chapter 1: General Information

Chapter 2: Scheme of B.Tech. CSE (Cyber Security) Syllabus
Chapter 3: Detailed Syllabus
Chapter 4: Guidelines for Internal assessment of Theory Courses.
4.1 Tools of assessment
4.2 Preparing sessional
4.3 Assignments
4.4 Computing Attainment Levels of COs
4.5 Submitting Internal Assessment Record
Chapter 5: Guidelines for Internal and External Assessment of Lab. Courses

Chapter 6: Guidelines for evaluating Industrial Training and Projects
Chapter 7: Computing PO attainment levels
Chapter1: General Information
Vision
Gurugram University aspires to be a front runner in global education; role model for
institutional excellence, trans-cultural quality learning, intellectual growth,
contemporary research, capacity building and nurturing socially and morally
responsible disciples through a learner- centric approach. The university seeks to
ensure a journey from studentship to epitome of discipleship by working on academic,
professional, technical, industry and life skills of its students.
Mission
1. To become a socially conscious centre of knowledge and advancement equipped to
take up the challenges of the global change as well as committed to empower its
teachers for the development of the students.
2. To move up through international alliances and collaborative initiatives to achieve

global excellence.
3. To create rigorous academic and research environment for creation of knowledge

and its perpetual advancement.
4. To attract and build people in a rewarding and inspiring environment by fostering

freedom, empowerment, creativity, scientific zeal and innovation.
DEPARTMENT OF ENGINEERING & TECHNOLGY
COMPUTER SCIENCE AND ENGINEERING
(Cyber Security)
VISION
MISSION
ABOUT THE PROGRAM

The Department of Computer Science and Engineering at Gurugram University in
Gurugram, Haryana, India, is an academic department that focuses on the study and
research of computer science and engineering disciplines. While Gurugram University
was established in 2017. The Department offers undergraduate postgraduate
programs and Doctorate in computer science and engineering. These programs aim to
provide students with a strong foundation in computer science principles, Artificial
Intelligence, Cyber Security and Internet of Things related areas.
The department likely offers a wide range of courses that cover various aspects of
computer science and engineering, such as data structures, operating systems,
computer networks, databases, artificial intelligence, machine learning, and more.
The curriculum is designed to equip students with the necessary knowledge and skills
to pursue careers in the IT industry, research and development, or further studies in
the field.
Moreover, the department may have well-qualified faculty members who are actively
engaged in research and teaching. They may have expertise in different areas of
computer science and engineering and may guide students in their academic pursuits
and research projects.
In addition to academic programs, the department also organize workshops,
seminars, and conferences to facilitate knowledge sharing and promote collaboration
among students, faculty, and industry professionals.
NOTE:
1. The scheme will be applicable from Academic Session 2022-23 onwards.
2. The scheme will also be applicable to the students who are admitted in 2022-23
academic session and are transiting in 3rd Semester of their program.
B.TECH. PROGRAM
(Cyber Security)
PROGRAM EDUCATION OBJECTIVES
To provide an in-depth understanding of the fundamentals of science and engineering
PEO1 concepts essential for a computer engineer and create a strong inception of lifelong
learning to facilitate progressive careers in industry and in pursuit of higher studies
To inculcate the knowledge of mathematical foundations with algorithmic principles
PEO2 and acquire technical and analytical skills to develop innovative solutions in solving
complex real life problems
To provide knowledge in computer science, modelling & design of computer based
PEO3 systems and make them skilled professional in the broad area of cyber security.
To impart knowledge to develop, analyze, evaluate, design, test and implement software
PEO4 required for various applications.
To equip our students with effective communication and personality skills, multi-
PEO5 disciplinary teamwork, become ethical and responsible engineer with fulfilling
societal responsibilities.
PROGRAM OUTCOMES
Engineering knowledge: Apply the knowledge of mathematics, science, engineering
PO1 fundamentals, and an engineering specialization to the solution of complex engineering
problems.
Problem analysis: Identify, formulate, review research literature, and analyze
PO2 complex engineering problems reaching substantiated conclusions using first
principles of mathematics, natural sciences, and engineering sciences.
Design/development of solutions: Design solutions for complex engineering problems
and design system components or processes that meet the specified needs
PO3
With appropriate consideration for the public health and safety, and the cultural,
societal, and environmental considerations.
Conduct investigations of complex problems: Use research-based knowledge and
PO4 research methods including design of experiments, analysis and interpretation of data,
and synthesis of the information to provide valid conclusions.
Modern tool usage: Create, select, and apply appropriate techniques, resources, and
PO5 modern engineering and IT tools including prediction and modeling to complex
engineering activities with an understanding of the limitations.
The engineer and society: Apply reasoning in formed by the contextual knowledge
PO6 To assess societal, health, safety, legal and cultural issues and the consequent
responsibilities relevant to the professional engineering practice.
Environment and sustainability: Understand the impact of the professional
PO7 engineering solutions in societal and environmental contexts, and demonstrate the
Knowledge of, and need for sustainable development.
Ethics: Apply ethical principles and commit to professional ethics and
PO8
responsibilities and norms of the engineering practice.
Individual and team work: Function effectively as an individual, and as a member or
PO9 leader in diverse teams, and in multidisciplinary settings.
Communication: Communicate effectively on complex engineering activities with the
engineering community and with society at large, such as, being able to
PO10
Comprehend and write effective reports and design documentation, make effective
presentations, and give and receive clear instructions.
Project management and finance: Demonstrate knowledge and understanding ofthe
engineering and management principles and apply these to one’s own work, as a
PO11 member and leader in a team, to manage projects and in multidisciplinary
environments.
Life-long learning: Recognize the need for, and have the preparation and ability to
PO12 engage in independent and life-long learning in the broadest context of technological
change.
PROGRAM SPECIFIC OUTCOMES
To understand, analyze and develop softwares and become proficient in the areas related
PSO1 to algorithms, networking, cyber security, web designing and apply their knowledge to
solve practical real-life problems.
To apply standard practices and strategies in IT security products for successful career
PSO2
and entrepreneurship.
To develop data, resource, and adopt asset protection strategies for organizations,
PSO3 processes, peoples, and individuals through Cybersecurity-centric skills.
Chapter2: Scheme of B.Tech CSE
(Cyber Security) Syllabus
GENERAL COURSE STRUCTURE & CREDIT DISTRIBUTION
MANDATORY INDUCTION PROGRAM (3-WEEKSDURATION)
When new students enter an institution, they come with diverse thoughts, backgrounds and preparations.
It is important to help them adjust to the new environment and inculcate in them the ethos of the institution
with a sense of larger purpose. A 3-week long induction program for the UG students entering the
institution, right at the start, has to be planned. Normal classes will start only after the induction program
is over. Its purpose is to make the students feel comfortable in their new environment, open them up, set
a healthy daily routine, create bonding in the batch as well as between faculty and students, develop
awareness, sensitivity and understanding of the self, people around them, society at large, and nature.
TentativeactivitieswhichcanbeplannedinthisInductionProgrammeareas follows:
1. Physical Activity
2. Creative Arts
3. Universal Human Values
4. Literary
5. Proficiency Modules
6. Lectures by Eminent People
7. Visits to Local Area
8. Familiarization to Dept./Branch &Innovations
Semester wise Structure and
Curriculum for
UG Course in
(Cyber Security)
(Engineering and Technology)
Gurugram University, Gurugram
GENERAL COURSE STRUCTURE & CREDIT DISTRIBUTION
STRUCTURE OF UNDERGRADUATE ENGINEERING PROGRAM
Breakup of Credits
S. No. Category
(Total 160)
1 Humanities and Social Sciences, including Management courses 8
2 Basic Science courses 25
Engineering Science courses including workshop, drawing, basics of
3 20.5
electrical/mechanical/computer etc.
4 Professional core courses 73
5 Professional Elective courses relevant to chosen specialization/branch 12
6 Open subjects – Electives from other technical and /or emerging subjects 12
7 Project work, seminar and internship in industry or elsewhere 16
Mandatory Courses [Environmental Sciences, Induction training,
8 Non-credit
Constitution of India, Essence of Indian Traditional Knowledge]
Total 166.5
SEMESTER-WISE SUMMARY OF THE PROGRAM

S. No. Semester No. of Contact Hours Credits Marks
1 I 26 19.5 900
2 II 27 22 900
3 III 26 22 1000
4 IV 26 21 900
5 V 29 25 1100
6 VI 26 22 900
7 VII 27 21 900
8 VIII 22 14 500
Total 209 166.5 7100
COURSE CODE AND DEFINITIONS

Course Code Definitions
L Lecture
T Tutorial
P Practical
BSC Basic Science Courses
ESC Engineering Science Courses
HSMC Humanities and Social Sciences, including Management courses
PCC Professional core courses
PEC Professional Elective courses
OEC Open Elective courses
LC Laboratory course
MC Mandatory courses
PROJ Project
CREDIT DISTRIBUTION IN THE FIRST YEAR OF THE
UNDERGRADUATE ENGINEERING PROGRAM
Bachelor of Technology
(Cyber Security)
HUMANITIES & SOCIAL SCIENCES, INCLUDING MANAGEMENT (HSMC)
S. No. Code No. Course Title Hours Per week Total Semester
L T P Credits
1. HSE-101 Communication Skills in 2 0 2 3 I
English
2. ENV - Basic of Environmental Science 2 0 0 2 I
101
3. HSV-102 Human Values and Soft Skills 2 0 2 3 II
Total Credits 8
BASIC SCIENCE COURSES (BSC)
Hours Per Week Total
S. No. Code No. Course Title Semester
L T P Credits
1. BSM - 101 Mathematics - I 3 1 0 4 I
2. BSP- 101 Physics 3 1 0 4 I / II
3. BSP-101P Physics (P) 0 0 2 1 I / II
4. BSM - 102 Mathematics - II 3 1 0 4 II
5. Discrete Mathematics 3 0 0 3 III
6. Aptitude Reasoning-I 3 0 0 3 III
7. Aptitude Reasoning-II 3 0 0 3 IV
8. Communication and Interpersonal 3 0 0 3 V
Skills
Total Credits 25
ENGINEERING SCIENCE COURSES (ESC)
Total
Hours Per Week Semester
S. No. Code No. Course Title Credits
L T P
EEE-101 Basics of Electrical and 3 0 0 3 I / II
1.
Electronics Engineering
EEE-101P Basics of Electrical and 0 0 2 1 I / II
2.
Electronics Engineering(P)
MEE- Workshop Practices (P) 1 0 3 2.5 I / II
3. 102P
CSE-101 Programming for Problem 3 0 0 3 I
4. Solving Using C
CSE-101P Programming for Problem 0 0 2 1 I
5.
Solving Using C (P)
CSE-103P Engineering Graphics (Web 1 0 2 2 I / II
6. Designing)
7. Digital Electronics 3 0 0 3 III
8. Digital Electronics (P) 0 0 2 1 III
9. R Programming 3 0 0 3 III
10. R Programming Lab (P) 0 0 2 1 III
Total Credits 20.5
PROFESSIONAL CORE COURSES (PCC)
Hours Per Week
S. No. Code No. Course Title Total
L T P Semester
Credits
1 CSE-102 Data Structure Using C 3 0 0 3 II
2 CSE-104 Object Oriented Concepts and 3 0 0 3 II
Python Programming
3 CSE-102P Data Structure Using C (P) 0 0 2 1 II
4 CSE-104P Object Oriented Concepts and 0 0 2 1 II
Python Programming (P)
5 Operating Systems 3 0 0 3 III
6 Introduction to Information 3 0 0 3 III
Security
7 Introduction to Information 0 0 2 1 III
Security (P)
8 Operating Systems Lab (P) 0 0 2 1 III
9 Computer Architecture and 3 0 0 3 IV
Organization
10 Analysis and Design of 3 0 0 3 IV
Algorithms
11 Analysis and Design of 0 0 2 1 IV
Algorithms Lab (P)
12 AI Data Analytics using R 3 0 0 3 IV
13 AI Data Analytics using R (P) 0 0 2 1 IV
14 Cryptography and Security 3 0 0 3 IV
15 Cryptography and Security Lab 0 0 2 1 IV
(P)
16 Soft Computing 3 0 0 3 IV
17 Database Management Systems 3 0 0 3 V
18 Database Management Systems 0 0 2 1 V
Lab (P)
19 Theory of Computation 3 0 0 3 V
20 Block Chain Technology 3 0 0 3 V
21 Block Chain Technology Lab (P) 0 0 2 1 V
22 Programming in JAVA 3 0 0 3 V
23 Programming in JAVA Lab (P) 0 0 2 1 V
24 Computer Networks 3 0 0 3 VI
25 Computer Networks Lab (P) 0 0 2 1 VI
26 Cyber Data Science and its 3 0 0 3 VI
application
27 Cyber Data Science and its 0 0 2 1 VI
application Lab (P)
28 Intrusion Detection Systems 3 0 0 3 VI
29 Text and Web Intelligence 3 0 0 3 VII
30 Text and Web Intelligence Lab 0 0 2 1 VII
(P)
31 Digital Forensics 3 0 0 3 VII
32 MOOC-1 3 0 0 3 VIII
33 MOOC-2 3 0 0 3 VIII
Total Credits 73
PROFESSIONAL ELECTIVE COURSES (PEC)
S. No. Code No. Course Title Hours Per Week Total Semester
Credits
L T P
1. Professional Elective Course - I 3 0 0 3 V
2. Professional Elective Course - II 3 0 0 3 VI
3. Professional Elective Course - 3 0 0 3 VI
III
4. Professional Elective Course - 3 0 0 3 VII
IV
Total Credits 12
OPEN ELECTIVE COURSES (OEC)

S. No. Code No. Course Title Hours Per Week Total
Credits Semester
L T P
1. Open Elective Course – I 3 0 0 3 V
2. Open Elective Course - II 3 0 0 3 VI
3. Open Elective Course - III 3 0 0 3 VII
4. Open Elective Course - IV 3 0 0 3 VII
Total Credits 12
PROJECT WORK, SEMINAR AND INTERNSHIP IN INDUSTRY OR ELSEWHERE
Hours per week Total
S. No. Code No. Course Title Semester
L T P Credits
1 Project-I 0 0 4 2 VI
2 Project-II 0 0 8 4 VII
3 Project-III / Industrial Project 0 0 16 8 VIII
4 Practical Training -I 0 0 2 1 V
5 Practical Training -II 0 0 2 1 VII
Total Credits 16
MANDATORY COURSES
S. No. Course Course Title Hours per week Total Semester
Code L T P Credits
1 Sports (Audit Course) 0 0 2 0 I
2 Indian Constitution 2 0 0 0 IV
Semester-wise Structure and
Curriculum for
UG Course in
Computer Science and
Engineering
(CYBER SECURITY)
B.Tech Computer Science and Engineering
(Cyber Security)
Scheme of Studies/Examination
Semester I
S. Category Course Code Course Title Hours per week Credits Marks Marks for Total
No. for End Term
Session Examination
L T P al
1 HSMC Communication Skills in 30 70 100
2 0 0 2
English
3 BSC Mathematics-I 3 1 0 4 30 70 100
4 ESC Basic of Electrical and 3 0 0 3 30 70 100

Electronics Engineering OR OR OR OR OR OR OR
OR Physics 3 1 0 4 30 70 100
5 ESC Programming for problem 30 70 100
3 0 0 3
solving using C
6 HSMC 30 70 100
Basics of Environmental
2 0 0 2
Science

0 0 2 1
English (P).
8 ESC 50 50
Basic of Electrical and 0 0 2 1 OR OR 100
Electronics Engineering OR OR OR OR 50 50 OR
(P) OR 0 0 2 1 100
Physics (P)
0 0 2 1
solving using C (P)
10 ESC
Workshop Practices (P) 1 0 50 50 100
3 2.5
OR OR OR OR OR OR
OR OR
Engineering Graphics 1 0 50 50 100
2 2
(Web Designing)
11 AU Sports (Audit Course) 0 0 0

0 0 2 0
Compulsory
Total 14 1 11 19.5 900
NOTE: The examination of the regular students will be conducted by the concerned college/Institute
internally. Each student will be required to score a minimum of 40% marks to qualify in the paper. The
marks will not be included in determining the percentage of marks obtained for the award of a degree.
However, these marks will be shown in the detailed marks certificate of the students.
B.Tech. Computer Science and Engineering
(Cyber Security)
Semester II
S. Category Course Course Title Hours per week Credits Marks Marks for Total
No. Code for End Term
Sessio Examination
L T P n al
1 BSC Mathematics-II 3 1 0 4 30 70 100
3 HSMC Human Value & Soft 30 70 100

2 0 2 3
Skills
OR Physics 3 1 0 4 30 70 100
5 PCC Data Structure Using C 3 0 0 3 30 70 100
6 PCC Object Oriented 30 70 100

Concepts and Python 3 0 0 3
Programming
7 ESC 50 50
(P) OR 0 0 2 1 100
Physics (P)
8 LC Data Structure Using C 50 50 100
0 0 2 1
(P)
9 LC Object Oriented 50 50 100
Programming (P)
10 ESC
3 2.5
OR OR OR OR OR OR
OR OR
2 2
(Web Designing)
Total 15 2 10 22 900
(Cyber Security)
Semester - III
No. for End Term
Session Examination
L T P al
1 ESC Digital Electronics 3 0 0 3 30 70 100
2 PCC Introduction to 3 0 0 3 30 70 100

Information Security
3 BSC Discrete 3 0 0 3 30 70 100
Mathematics
4 ESC R Programming 3 0 0 3 30 70 100
5 PCC Operating 3 0 0 3 30 70 100

Systems
6 LC Digital Electronics 0 0 2 1 50 50 100
(P)
7 LC Introduction to 0 0 2 1 50 50 100
(P)
8 LC R Programming (P) 0 0 2 1 50 50 100
9 LC Operating Systems (P) 0 0 2 1 50 50 100
10 BSC Aptitude Reasoning- I 3 0 0 3 30 70 100
Total 18 0 8 22 1000
(Cyber Security)
Semester - IV
No Code for End Term
. Session Examination
L T P al
1 BSC Aptitude Reasoning -II 3 0 0 3 30 70 100
2 PCC Computer Architecture 3 0 0 3 30 70 100
and Organization
3 PCC Analysis and Design 3 0 0 3 30 70 100
of Algorithms
4 PCC AI Data Analytics 3 0 0 3 30 70 100
using R
5 PCC Cryptography and 3 0 0 3 30 70 100
Security
6 PCC Soft Computing 3 0 0 3 30 70 100
7 LC Cryptography and 0 0 2 1 50 50 100
Security Lab (P)
8 LC Analysis and Design of 0 0 2 1 50 50 100
Algorithms Lab (P)
9 LC AI Data Analytics using 0 0 2 1 50 50 100
R Lab (P)
10 AU Indian Constitution* 2 0 0 0 Refer Note: 1 (Grading)
Total 20 0 6 21 900
NOTE: The examination of the regular students will be conducted by the concerned college/Institute internally.
Each student will be required to score a minimum of 40% marks to qualify in the paper. The marks will not be
included in determining the percentage of marks obtained for the award of a degree. However, these marks will
be shown in the detailed marks certificate of the students.
(Cyber Security)
Semester - V
S. Category Course Course Title Hours per Credit Marks Marks for Total
No Code week s for End Term
. Session Examinatio
L T P
al n
1 PCC Database Management
3 0 0 3 30 70 100
Systems
2 PCC Theory of Computation 3 0 0 3 30 70 100
3 PCC Programming in JAVA 3 0 0 3 30 70 100
4 PCC Block Chain Technology 3 0 0 3 30 70 100
5 OEC Open Elective I 3 0 0 3 30 70 100
6 PEC Professional Elective I 3 0 0 3 30 70 100
7 BSC Communication and
3 0 0 3 30 70 100
Interpersonal Skills
8 LC Database Management
0 0 2 1 50 50 100
Systems Lab (P)
9 LC Programming in JAVA
0 0 2 1 50 50 100
Lab (P)
10 LC Block Chain Technology
0 0 2 1 50 50 100
Lab (P)
Practical Training-I 0 0 2 1 50 50 100
Total 21 0 8 25 1100
NOTE:
1. Choose any one from Professional Elective Course – I
2. Choose any one from Open Elective Course – I *
Professional Elective Course – I

1. Introduction to Physical and Systems Security
2. Software Security and Trusted Systems
3. Biometrics
4. Cyber Security Threats
* Open Elective Course – I

To be chosen from the bucket of Open Elective Course-I
(Cyber Security)
Semester - VI
L T P al
1 PCC Computer 3 0 0 3 30 70 100
Networks
2 PCC Cyber for Data
Science and its 3 0 0 3 30 70 100
applications
3 PCC Intrusion Detection 3 0 0 3 30 70 100
Systems
4 PEC Professional
3 0 0 3 30 70 100
Elective –II
5 OEC Open-Elective-II 3 0 0 3 30 70 100
PEC Professional 3 0 0 3 30 70 100
Elective -III
7 LC Computer 0 0 2 1 50 50 100
Networks Lab (P)
8 LC Cyber for Data 0 0 2 1 50 50 100
Science and its
applications Lab (P)
9 PROJ Project-I 0 0 4 2 50 50 100
Total 18 0 8 22 900
NOTE:
1. At the end of the 6th semester, each student has to undergo Practical Training of 4/6 weeks in an
Industry/ Institute/ Professional Organization/ Research Laboratory/ training center etc. and
submit the typed report along with a certificate from the organization & its evaluation shall be
carried out in the 7th Semester.
2. Choose any one from Professional Elective Course – II & III
3. Choose any one from Open Elective Course – II*
Professional Elective Course – II
1. Cyber Crimes and Laws
2. Database and Cloud Security
3. Malware Analysis and Reverse Engineering
4. Steganography & Digital Watermarking
Professional Elective Course – III
1. Software Testing and Project Management
2. Data Mining and Warehousing
3. Social network Analysis
4. Cryptocurrency with ethereum
*Open elective Course-II : To be chosen from the bucket of Open Elective Course-II
(Cyber Security)
Semester - VII
L T P al
1 PCC Text and Web 3 0 0 3 30 70 100
Intelligence
2 LC Text and Web 0 0 2 1 50 50 100
Intelligence (P)
3 PCC Digital Forensics 3 0 0 3 30 70 100
4 PEC Professional 3 0 0 3 30 70 100
Elective-IV
5 OEC Open Elective-III 3 0 0 3 30 70 100
6 OEC Open Elective-IV 3 0 0 3 30 70 100
7 Project Project-II 0 0 8 4 100 100 200
8 Training Practical Training-II 0 0 2 1 50 50 100
Total 15 0 12 21 900
NOTE:
1. Choose any one from Professional Elective Course – IV
2. Choose any one from Open Elective Course – III & IV
Professional Elective Course – IV

1. Ethical Hacking
2. Information Security Risk Assessment
3. Wireless and Mobile security
4. Wireless sensor networks
* Open Elective Course – III & IV : To be chosen from the bucket of Open elective –III and IV
respectively
(Cyber Security)
Semester - VIII
S. Category Course Course Title Hours per Credits Marks Marks for Total
No Code week for End Term
L T P
al n
1 PROJ Project III/Industrial 0 0 16 8 150 150 300
Project
2 MOOC 3 0 0 3 30 70 100
3 MOOC 3 0 0 3 30 70 100
9
Total 06 16 14 210 290 500
NOTE: At the end of the 8th semester, each student has to submit the certificate of MOOCs (Essential).
Chapter 3: Detailed Syllabus
B.Tech Computer Science and Engineering
(Cyber Security)
Semester I
No. for End Term
Session Examination
L T P al
2 0 0 2
English
3 BSC Mathematics-I 3 1 0 4 30 70 100

OR Physics 3 1 0 4 30 70 100
3 0 0 3
solving using C
6 HSMC 30 70 100
Basics of Environmental
2 0 0 2
Science

0 0 2 1
English (P).
8 ESC 50 50
(P) OR 0 0 2 1 100
Physics (P)
0 0 2 1
solving using C (P)
10 ESC
3 2.5
OR OR OR OR OR OR
OR OR
2 2
(Web Designing)
11 AU Sports (Audit Course) 0 0 0

0 0 2 0
Compulsory
Total 14 1 11 19.5 900
Course code HSE-101
Category Humanities and Social Sciences
Course title Communication Skills in English
L T P Credits
Scheme and Credits
2 0 0 2
Class work/ Practical 30 Marks
Exam 70 Marks
Total 100 Marks
Duration of Exam 03 Hours
COURSE OUTCOMES:
1. The course will focus on the four integral skills of language, improving the proficiency
levels in all of them and to learn to use language as a tool for effective
communication.
2. The course will focus on the four integral skills of language, improving the proficiency
levels in all of them and to learn to use language as a tool for effective
communication
3. This course will widen the understanding of the learners in all genres of literature
(short stories, poetry, autobiographies.) with the help of expository pieces .
4. The course will strive to equip the learner with the ability to express oneself and be
understood by others with clarity and precision, in both written and spoken forms.
5. This course will encourage creative use of language through translation,
paraphrasing and paragraph writing.
6. Along with the above, the course will also build confidence and encourage the
students to use a standard spoken form of English in order to prepare them to face
job interviews, workplace and in higher studies.
UNIT-I
Remedial English : Parts of speech, Gerunds, Participles and infinitives; Clauses; Sentence constructions
(unity; avoidance of choppy and rambling sentences, logic and consistency, conciseness, sequencing of
ideas); Sentence errors-agreement between verb and subject, pronoun and antecedents, sequence of tenses,
problems involving modifiers (dangling and misplaced modifiers); Shifts in point of view consistency of
number and person, tense, mood, voice and subject; Parallelism; Omissions and mixed constructions.
UNIT-II
Vocabulary : Methods of building vocabulary-etmological roots, prefixes and suffixes; Commonly used
foreign words and phrases; spelling; words often confused synonyms and homonyms; one word
substitutes; verbal idioms.
UNIT-III
Punctuation and Mechanics: End Punctuation; internal Punctuation; Word Punctuation. Comprehension:
Abstracting; Summarizing; Observation, Findings and Conclusions; Illustration and Inductive Logic;
Deduction and Analogy.
UNIT-IV
Presentation: Oral presentation- Extempore, discussion on topics of contemporary relevance, Interviews.
Written Comprehension: The ability to write after listening to and reading select speeches, news bulletins,
presentations and answering questions based on what has been heard. Reading the given texts to skim,
scan, infer and answer comprehension questions. Reading texts like case studies and project reports for
critical assessment and book Review.
Suggested Books:
1. Nitin Bhatnagar and Mamta Bhatnagar, Communicative English for Engineers and Professionals.
Pearson Education.
2.Bhatnagar, k. Manmohan.Ed. The Spectrum of Life: An Anthology of Modern Prose. Delhi:
Macmillan India Ltd., 2006.
3 C. Murlikrishna& Sunita Mishra, Communication Skills for Engineers, Pearson Ed.
4 Sinha, R.P.Current English Grammar and Usage. OUP.
5.Rizvi, M. Ashraf.Effective Technical Communication. McGraw Hill Education (India) Pvt. Ltd.,
2014.
6.Eastwood, John.Oxford Guide to English Grammar.OUP, 2010.
7.Kumar, Sanjay and PushpLata. Communication Skills. OUP, 2011.
8. Raman, Meenakshi and Sangeeta Sharma.CommunicationSkills.NewDelhi:OUP,2011.
9.Hill, L.A.A Guide to Correct English.London:OUP,1965.
10.Oxford Dictionary of English Idioms. New Delhi: OUP, 2009
11*http://yousigma.com/religionandphilosophy/swamivivekananda/thescecretofwork.pdf
Course Code BSM-101

Category Basic Science Course
Course title Mathematics-I
L T P Credits
Scheme and Credits
3 1 0 4
Class work 30 Marks
Exam 70 Marks
Total 100 Marks
COURSE OBJECTIVES
1. To develop logical understanding of the subject

2. To develop mathematical skill so that students are able to apply mathematical methods &
principals in solving problem from Engineering fields.
3. To make aware students about the importance and symbiosis between Mathematics and
Engineering.
UNIT-I
Matrices: Matrices, Vectors: addition and scalar multiplication, Matrix multiplication, Linear systems of
equations, Linear Independence, Rank of a matrix, Determinants, Cramer’s Rule, Inverse of a matrix,
Gauss elimination and Gauss-Jordan elimination.
UNIT-II
Vector spaces I: Vector Space, Linear dependence of vectors, Basis, Dimension, Range and kernel, Rank
and nullity, Inverse of a linear transformation, Rank nullity theorem,
UNIT-III
Vector spaces II: Eigenvalues, Eigenvectors, Symmetric, Skew-symmetric and Orthogonal Matrices,
Eigen bases, Diagonalization, Inner product spaces, Gram-Schmidt orthogonalization.
UNIT-IV
Calculus: Indeterminate forms and L' Hospital's rule, Rolle’s Theorem, Mean value theorems, Taylor’s
and Maclaurin theorems, Evaluation of definite and improper integrals, Applications of definite integrals
to evaluate surface areas and volumes of revolutions, Beta and Gamma functions and their properties.
Reference Books:
1. G.B. Thomas and R.L. Finney, Calculus and Analytic geometry, Pearson Education.
2. Erwin Kreyszig, Advanced Engineering Mathematics, John Wiley & Sons.
3. D. Poole, Linear Algebra: A Modern Introduction, Brooks Cole.
4. Ramana B.V., Higher Engineering Mathematics, Tata McGraw-Hill Publishing Company Limited.
5. N.P. Bali and Manish Goyal, A text book of Engineering Mathematics, Laxmi Publications.
6. B.S. Grewal, Higher Engineering Mathematics, Khanna Publishers.
Course code BSP-101

Course title Physics

L T P Credits
Scheme and Credits
3 1 0 4
Class work 30Marks
Exam 70 Marks
Total 100 Marks
UNIT – I
Review of Atomic Structure and Statistical Mechanics: - Ideas on Atomic Structure, Quantum Mechanics,
The Schrodinger Wave Equation, Statistical Mechanics, Bonding of atoms, Crystalline state. Free electron
theory, Density of states and energy band diagrams, Kronig-Penny model (to introduce origin of band
gap), Energy bands in solids, E-k diagram, Direct and indirect band gaps, Types of electronic materials:
metals, semiconductors, and insulators, Density of states, Occupation probability, Fermi level, Effective
mass, Phonons.
UNIT - II
Elemental and compound semiconductors, Intrinsic and extrinsic semiconductors, Dependence of Fermi
level on carrier-concentration and temperature (equilibrium carrier statistics), Carrier generation and
recombination, Carrier transport: diffusion and drift, The Hall Effect, Einstein Relations, Excess carriers
in semiconductors p-n junction, Excess carriers and Quasi-Fermi Levels, Basic equations for
semiconductor device operation, Solution of carrier transport equation.
UNIT - III
P-N Junctions: - The abrupt junction (Electric field, potential, capacitance), V-I characteristic of an ideal
diode, a real diode. Metal-semiconductor junction (Ohmic and Schottky), Semiconductor materials of
interest for optoelectronic devices.
Optical transitions in bulk semiconductors: absorption, spontaneous emission, and stimulated emission;
Joint density of states, Density of states for photons, Transition rates (Fermi's golden rule), Optical loss
and gain; Photovoltaic effect, Exciton, Drude model.
UNIT - IV
Four-point probe and van der Pauw measurements for carrier density, resistivity, and hall mobility; Hot-
point probe measurement, capacitance-voltage measurements, parameter extraction from diode I-V
characteristics, DLTS, band gap by UV-Vis spectroscopy, absorption/transmission.
Densityofstatesin2D, 1D and 0D (qualitatively). Practical examples of low-dimensional systems such as
quantum wells, wires, and dots: design, fabrication, and characterization techniques. Heterojunctions and
associated band- diagram.
Suggested reference books
1. Pierret, Semiconductor Device Fundamental,

2. P. Bhattacharya, Semiconductor Optoelectronic Devices, Pearson Education
3. J. Singh, Semiconductor Optoelectronics: Physics and Technology, McGraw-HillInc.
4. B.E.A. Saleh and M.C. Teich, Fundamentals of Photonics, John Wiley & Sons, Inc.
5. S. M. Sze, Semiconductor Devices: Physics and Technology, Wiley
6. A. Yariv and P. Yeh, Photonics: Optical Electronics in Modern Communications, Oxford
University Press, New York.
7. Online course: “Semiconductor Optoelectronics” by M R Shenoy on NPTEL
8. Online course: "Optoelectronic Materials and Devices" by Monica Katiyar and Deepak Gupta on
NPTEL
Course code EEE-101

Category Engineering Science Course
Course title Basics of Electrical and Electronics Engineering
L T P Credits
Scheme and Credits
3 0 0 3
Class work 30 Marks
Exam 70 Marks
Total 100 Marks
COURSE OBJECTIVES
1. To provide basic knowledge of different elements of electrical and electronics engineering field.
2. To familiarize the students with the concepts of electrical circuits and network Analysis.
3. To understand the basics of AC and DC circuits.
4. To familiarize students to the analysis and design of analog electronic circuits which form the
basic building blocks of almost any electronic system.
5. To introduce p-n junction theory, operation of the semiconductor devices and their use in basic
electronic circuits.
UNIT-I
DC Circuits: Role and importance of circuits in Engineering, Concept of fields, charge, current, voltage,
energy and their interrelationships. Electrical circuit elements (R, L and C), voltage and current sources
(ideal & Controlled) series and parallel circuits, Network reduction: voltage and current division
Kirchhoff current and voltage laws with their applications (Nodal and Mesh Analysis), Source
transformation - star delta conversion. Superposition theorem, Thevenin and Norton Theorems, Millman,
Substitution and Reciprocity theorem.
UNIT-II
AC Circuits: Representation of sinusoidal waveforms, average, peak and rms values, complex
representation of impedance, phasor representation, complex power, real power, reactive power, apparent
power, power factor and Energy, Analysis of single-phase ac circuits consisting of R, L, C, RL, RC, RLC
combinations (series and parallel),Resonance; Introduction to three- phase circuits
UNIT-III
Introduction to p-n junction diode and its pplications. Half wave & full wave rectifiers. clipping and
clamping circuits, Varactor, Varistor, Voltage Regulator
Bipolar junction transistors and its biasing BJT operation, BJT voltages and currents, CE, CB and CC
characteristics, DC load line and bias point, base bias, emitter feedback bias, collector feedback bias,
voltage divider bias, Thermal stability, biasing BJT switching circuits, transistor power dissipation and
switching time, Testing of bipolar junction transistor with multi-meter, Reading datasheet of BJT.
UNIT-IV
Field Effect Devices: JFET : basic Operation and characteristics, drain and transfer characteristics, pinch
off voltage, parameters of JFET: Transconductance (gm), ac drain resistance (rd), amplification factor(μ)
,Small Signal Model & Frequency Limitations. MOSFET: basic operation, depletion and enhancement
type, pinch-off voltage, Shockley equation and Small Signal Model of MOSFET, MOS capacitor.
Suggested books:
1. E. Huges, “Electrical Technology”, ELBS.

2. J. Millman and C. Halkias, Integrated Electronics, McGraw Hill, 2ndEdition, 2009.
3. M.M. Mano: Digital Logic Design, Phi.
1. D. P. Kothari and I. J. Nagrath, “Basic Electrical Engineering”, Tata McGraw Hill, 2010.
2. V. Del Toro, “Principles of Electrical engineering”, PHI.
3. A. Sedra and C. Smith, Microelectronic Circuits: Theory and Applications, Oxford
University Press, 6thEdition, 2013.
4. Boylestad and Nashelsky, “Electronic Devices and Circuit Theory” Pearson publishers,
10thEdition
5. R.P. Jain: Modern Digital Electronics, Tmh.
6. Malvino and Leach, ” Digital Principles and Applications”, TMH publishers, 8thEdition
7. Tyagi M.S., “Introduction to Semiconductor Materials and Devices”, John Wiley & Sons,
1993.
8. Basic Electrical Engineering, A.E. Fitzgerald , David Higginbotham 2009 , Arvin Grabel,
Tata McGraw-Hill Publishing Company; 5thEdition.
Course code CSE-101

Category Professional Core Course
Course title Programming for Problem Solving Using C
L T P Credits
Scheme and Credits
3 0 0 3
Class work 30 Marks
Exam 70 Marks
Total 100 Marks
UNIT-I
Introduction to Programming: Idea of Algorithm: Steps to solve logical and numerical problems.
Representation of Algorithm: Flowchart/Pseudocode with examples. C Programming: Keywords,
Variables and Data Types: basic, derived and user defined, Type Conversions, Header Files, Basic Input
and Output Functions and Statements, Compilation, Syntax and Logical Errors in compilation, Object and
Executable Code, Storage Classes, Arithmetic Expressions and Precedence.
UNIT-II
Preprocessors, Conditional and Branching Statements, Loops/ Iterative Statements, Writing and
evaluation of conditionals and consequent branching.
UNIT-III
Arrays (1-D, 2-D), Character Arrays and Strings, Arrays with Pointers, Functions (including using built
in libraries), Parameter passing in functions, Call by Value, Call by Reference, Passing arrays to functions,
Recursion, as a different way of solving problems. Example programs, such as Finding Factorial,
Fibonacci series, Ackerman function etc.
UNIT-IV
Idea of pointers, Defining pointers, Use of Pointers in self-referential structures, Introduction to Dynamic
Memory Allocation and its Methods, Structures, Union, Defining Structures and Array of Structures, File
Handling.
Suggested Text Books:

1. Ajay Mittal, Programming in C, ‘A Practical Approach’, Pearson Education.
2. Byron Gottfried, Schaum's Outline of Programming with C, McGraw-Hill
3. E. Balaguruswamy, Programming in ANSI C, Tata McGraw-Hill
4. Yashavant Kanetkar, Let Us C, BPB Publication.
5. Gill, Nasib Singh: Computing Fundamentals and Programming in C, Khanna Book Publishing
Company(Private) Limited, New Delhi
Suggested Reference Books

1. Brian W. Kernighan and Dennis M. Ritchie, The C Programming Language, Prentice Hall of India.
Course code ENV-101
Course title Basics of Environmental Science
L T P Credits
Scheme and Credits
2 0 0 2
Class work/Practical 50Marks
Exam 50Marks
Total 100Marks
COURSE OBJECTIVES:
1. To impart the knowledge and awareness for the environmental protection for real-time
contribution during an execution of engineering practices in the society.
COURSE OUTCOMES:
1. To understand the basic concepts of environmental studies and natural resources.

2. To learn about the various eco-systems of nature.
3. To gain knowledge about different types of environmental pollutions and their control
4. measures.
6. To acquire the knowledge about the various social aspects related to the environment.
UNIT-I
Environmental studies and Natural Resources: Definition, scope and importance of environmental
studies.
Natural Resources: Renewable and non-renewable resources, and associated problems
(a) Forest resources: Use and over-exploitation, deforestation, Timber extraction, mining, dams and their
effects on forests and tribal people.
(b)Water resources: Use and over-utilization of surface and ground water, floods, drought, conflicts over
water, dam’s benefits and problems.
(c) Mineral Resources: Use and exploitation, environmental effects of extracting and using mineral
resources.
(d)Food Resources: World food problems, changes caused by agriculture and over grazing, effects of
modern agriculture, fertilizers-pesticides problems, water logging, salinity.
(e) Energy Resources: Growing energy needs, renewable and non-renewable energy sources, use of
alternate energy sources.
UNIT-II
Eco Systems: Concept of an eco-system, Structure and function of an eco-system, Producers, consumers,
decomposers, Energy flow in the ecosystems, Ecological succession, Food chains, food webs and
ecological pyramids.
Introduction, types, characteristic features, structure and function of the following ecosystems:
(a) Forest ecosystem
(b) Grass land ecosystem
(c) Desert ecosystem
(d) Aquatic eco systems (ponds, streams, lakes, rivers, oceans, estuaries)
UNIT-III
Environmental Pollution: Definition, Causes, effects and control measures of;
(a) Air pollution
(b) Soil pollution
(c) Marine pollution
(d) Noise pollution
(e) Nuclear hazards
Disaster management: Floods, earth quake, cyclone and landslides.
UNIT-IV
Social issues and the Environment: From unsustainable to sustainable development, Urban problems
related to energy, Water conservation, rain water harvesting, watershed management.
Environmental ethics: issues and possible solutions, Climate change, global warming, acid rain, ozone
layer depletion, nuclear accidents and holocaust. Environment protection Act, Air (prevention and control
of pollution) Act, Water (prevention and control of pollution) Act, Wildlife protection Act, Forest
conservation Act, Issues involved in enforcement of environmental legislations.
Recommended Books:
1. Textbook of Environmental studies, Erach Bharucha, UGC.
2. Fundamental concepts in Environmental Studies, D. D. Mishra, S Chand & Co Ltd.
Course code HSE-101P

Course title Communication Skills in English (P)
L T P Credits
Scheme and Credits
0 0 2 1
Class work/ Practical 50 Marks
Exam 50 Marks
Total 100 Marks
Communication Skills in English (P)
Lab Activity: The students will acquire basic proficiency in English with special emphasis on listening,
comprehension and speaking skills both at social and professional platforms.
(i) Listening comprehension
(ii) Recognition of phonemes in International Phonetic Alphabet
(iii) Self introduction and introduction of another person
(iv) Conversation and dialogues in common everyday situations
(v) Communication at work place (Standard phrases and sentences in various situations)
(vi) Telephonic communication
(vii) Speeches for special occasions (Welcome speeches, Introduction speeches, Felicitation
speeches and Farewell speeches)
(viii) Tag Questions
(ix) Formal Presentations on literary texts prescribed in theory paper, Question Formation & Mock
Press Conference
Course code BSP-101P
Course title Physics (P)

L T P Credits
Scheme and Credits
0 0 2 1
Class work 50 Marks
Exam 50 Marks
Total 100 Marks
Note: At least 8 experiments are to be performed by the students.
List of Subject related Experiments:
1. To study the forward and reverse characteristics of P-N junction diode.

2. To study the characteristics of Solar cell and find out the fill factor..
3. To study the reverse characteristics of Zener diode and voltage regulation using Zener Diode.
4. To determine Planks constant using photocell.
5. To measure e/m of electron using helical method.
6. To find capacitance of condenser using fleshing and quenching experiment.
7. To find temperature co-efficient of platinum using Callender Griffith bridge.
8. To find out low resistance by Carry Foster bridge.
9. To find resistance of galvanometer by post office box.
10. To measure resistance using four probe methode.
11. To compare the capacitance of two capacitors using De‘Sauty Bridge.
Course code EEE-101P

Course title Basics of Electrical and Electronics Engineering (P)
L T P Credits
Scheme and Credits
0 0 2 1
Class work 50 Marks
Exam 50 Marks
Total 100 Marks

1. Verify that resistance of conductor is directly proportional to resistivity and length and
inversely proportional to cross- sectional area of the conductor.
2. Verification of Ohm’s Law, Kirchhoff current and voltage laws
3. Verification of temperature co-efficient of resistance: (i) Positive for Tungsten and
Nichrome and (ii) Negative for carbon.
4. To measure DC voltage and current, AC voltage and current with multi-meter
5. To observe waveforms on oscilloscope, measure basic parameters amplitude and
frequency of sine wave and square wave.
6. Obtain VI characteristics of semiconductor rectifier diode, LED, Photo-diode
7. To observe waveform at the output of half wave rectifier with and without filter capacitor.
8. To observe waveform at the output of full wave rectifier with and without filter capacitor.
9. To experimentally plot the input and output characteristics of a given BJT transistor in CE
configuration and calculate its various parameters.
10. To experimentally plot the input and output characteristics of a given BJT transistor in CB
configuration and calculate its various parameters.
11. To study the transfer and drain characteristics of JFET and calculate its various parameters.
12. To study the transfer and drain characteristics of MOSFET and calculate its various
parameters.
Course code CSE-101P

Course title Programming for Problem Solving Using C (P)
L T P Credits
Scheme and Credits
0 0 2 1
Class work 50 Marks
Exam 50 Marks
Total 100 Marks
LABORATORY OUTCOMES
1. To formulate the algorithms for simple problems

2. To translate given algorithms to a working and correct program
3. To be able to correct syntax errors as reported by the compilers
4. To be able to identify and correct logical errors encountered at run time
5. To be able to write iterative as well as recursive programs
6. To be able to represent data in arrays, strings and structures and manipulate them through a
program
Tutorial 1: Problem solving using computers:

Lab1: Familiarization with programming environment
Tutorial 2: Variable types and type conversions:

Lab 2: Simple computational problems using arithmetic expressions
Tutorial 3: Branching and logical expressions:

Lab 3: Problems involving if-then-else structures
Tutorial 4: Loops, while and for loops:

Lab 4: Iterative problems e.g., sum of series
Tutorial 5: 1D Arrays
Lab 5: 1D Array manipulation
Tutorial 6: 2D arrays and Strings

Lab 6: Matrix problems, String operations
Tutorial 7: Functions, call by value:

Lab 7: Simple functions

Course title Engineering Graphics (Web Designing)
L T P Credits
Scheme and Credits
1 0 2 2
Class work 50 Marks
Exam 50 Marks
Total 100 Marks
SYLLABUS
Brief history of Internet, introduction to world wide web, basic principles involved in developing a web
site, rules of web designing, web standards, audience requirements, Design concept.
Introduction to elements of HTML, XHTML and CSS.
Javascript as programming language, Language Syntax: Data types, Values, Variables, Expressions
and Operators. JavaScript Statements, loops, arrays, strings, methods, Defining and Invoking functions
and their closure.
Introduction of Google Web Designer, Firefox, Wordpress, sublime text, Angular.JS, jQuery etc.
Lab work
1. Prepare a survey document of ten website which you like and dislike with various reasons.
(Prerequisite )
2. Introduction to basic HTML elements
3. Use table tag to format web page. Also create the Time Table of your class using table tag.
4. Create your profile page i.e. educational details, Hobbies, Achievement, My Ideals etc.
5. Create Style sheet to set formatting for text tags and embed that style sheet on web pages created
for your site. Design a web page and embed various multimedia features in the page.
6. Design signup form to validate username, password, and phone numbers etc using Java script.
7. Write a JavaScript program to determine whether a given year is a leap year in the Gregorian
calendar.
8. Write a JavaScript program to convert temperatures to and from celsius, Fahrenheit.
9. Installation of Wordpress and designing the wordpress site.
10. Introduction to Dreamweaver and setting up site using Dreamweaver.
11. Submission of Website with Report.
Course code MEE-102P

Course title Workshop Practices (P)
L T P Credits
Scheme and Credits
1 0 3 2.5
Class work 50 Marks
Exam 50 Marks
Total 100 Marks
COURSE OBJECTIVES
1. To impart fundamental Knowledge of engineering practices such as fitting, wood working, foundry,
machining, welding, etc. for manufacturing a product.
2. To prepare the students to understand the various tools and equipment’s used in these processes and
their working principle
3. To impart fundamental Knowledge of Lathe machine
4. To able to understand the basic knowledge of various welding processes
SYLLABUS
Introduction:
Introduction to Manufacturing Processes and their Classification, Introduction to additive manufacturing,
Industrial Safety.
Machining Shop:
Lathe, description of lathe: headstock, tailstock, gearbox, carriage, apron, cutting speed, feed & depth of
cut, cutting tools, Chucks: 3 jaw, 4 jaw.
Fitting shop:
Introduction, classification of metals: ferrous and nonferrous, fitting tools: measuring and marking tools,
marking schemes for a fitting jobs, cutting tools.
Carpentry shop:
Introduction of carpentry, types of woods, carpentry tolls: measuring tools, marking tolls, cutting tools:
saws, chisels, planning tools, drilling tools, striking tools, drilling tools, wood working joints, wood
working lathe.
Foundry Shop:
Introduction, foundry hand tools, measuring boxes, ladle, moulding, furnaces,Types of Pattern and
Allowances
Welding Shop:
Introduction to welding, Classification of Welding Processes, Arc welding & Gas welding equipment’s.
Reference Books:
1. S K Hajra Choudhury, Nirjhar Roy, A K Hajra Choudhury, Elements of workshop Technology (vol.
1&2), Media Promoters.
2. B S Raghuwanshi, A Course in Workshop Technology (manufacturing Process vol. 1& 2) Dhanpat
Rai & CO.
3. O.P. Khanna, Workshop Technology. Dhanpat Rai Publication.
4. W A J Chapman, Workshop technology in SI unit (part – 1 &2), Mc Graw Hill Education.
5. M.P. GROOVER, Principles of Modern Manufacturing, Wiley.
6. Kalpakjian, Manufacturing Process for Engineering Materials, Pearson Education India.
Lab Work
List of Experiments
1. To study different types of measuring tools used in metrology and determine least counts of vernier
callipers, micrometres and vernier height gauges.
2. To study different types of machine tools (lathe, shaper, planer, milling, drilling machines)
3. To prepare a job on a lathe involving like facing, outside turning, taper turning, step turning, radius
making and parting-off.
4. To study different types of fitting tools and marking tools used in fitting practice.
5. To prepare a job made out of MS Flats, making saw – cut filling V-cut taper at the corners.
6. To prepare lay out on a metal sheet by making and prepare rectangular tray pipe shaped components
e.g. funnel.
7. To prepare joints for welding suitable for butt welding and lap welding.
8. To study various types of carpentry tools and prepare simple types of at least two wooden joints.
9. To prepare simple engineering components/shapes by forging.
10. To prepare mold and core assembly.
11. To prepare horizontal surface/vertical surface/curved surface/slats or V-grooves on a shaper/planner.
12. To prepare a job involving side and face milling on a milling
13. To prepare a job on CNC Machine/Additive Manufacturing.
Note : At least eight experiments/jobs are to be performed/prepared by the students in the semester.
(Cyber Security)
Semester II
Sessio Examination
L T P n al
1 BSC Mathematics-II 3 1 0 4 30 70 100
3 HSMC Human Value & Soft 30 70 100

2 0 2 3
Skills
OR Physics 3 1 0 4 30 70 100
5 PCC Data Structure Using C 3 0 0 3 30 70 100
6 PCC Object Oriented 30 70 100

Programming
7 ESC 50 50
(P) OR 0 0 2 1 100
Physics (P)
8 LC Data Structure Using C 50 50 100
0 0 2 1
(P)
9 LC Object Oriented 50 50 100
Programming (P)
10 ESC
3 2.5
OR OR OR OR OR OR
OR OR
2 2
(Web Designing)
Total 15 2 10 22 900
NOTE: The examination of the regular students will be conducted by the concerned college/Institute internally.
Each student will be required to score a minimum of 40% marks to qualify in the paper. The marks will not be
included in determining the percentage of marks obtained for the award of a degree. However, these marks will be
shown in the detailed marks certificate of the students
Course Code BSM-102
Course title Mathematics-II
L T P Credits
Scheme and Credits
3 1 0 4
Class work 30Marks
Exam 70 Marks
Total 100 Marks
COURSE OBJECTIVES
1. Demonstrate their understanding of mathematical ideas from multiple perspectives.

2. To develop logical understanding of the subject
3. To develop mathematical skill so that students are able to apply mathematical methods &
principals in solving problem from Engineering fields.
4. To make aware students about the importance and symbiosis between Mathematics and
Engineering.
UNIT-I
Random variables and discrete probability distributions: Conditional probability, Probability spaces,
Discrete random variables, Independent random variables, Expectation of discrete random variables,
Sums of independent random variables, Moments, Variance of a sum, Correlation coefficient,
Chebyshev's Inequality, The multinomial distribution, Poisson approximation to the binomial distribution,
Infinite sequences of Bernoulli trials.
UNIT-II
Continuous and Bivariate probability distribution: Continuous random variables and their properties,
Distribution functions and densities, Normal, Exponential and Gamma densities, Bivariate distributions
and their properties, Distribution of sums and quotients, Conditional densities, Bayes' rule.
UNIT-III
Basic Statistics: Measures of Central tendency: Moments, Skewness and Kurtosis - Probability
distributions: Binomial, Poisson and Normal - evaluation of statistical parameters for these three
distributions; Correlation and regression – Rank correlation; Curve fitting by the method of least squares-
fitting of straight lines, second degree parabolas and more general curves.
UNIT-IV
Applied Statistics: Test of significance: Large sample test for single proportion, difference of
proportions, single mean, difference of means, and difference of standard deviations; Small samples: Test
for single mean, difference of means and correlation coefficients; Test for ratio of variances – Chi-square
test for goodness of fit and independence of attributes
Reference Books:
1. Erwin Kreyszig, Advanced Engineering Mathematics, John Wiley & Sons.

2. P. G. Hoel, S. C. Port and C. J. Stone, Introduction to Probability Theory, Universal Book
Stall.
3. S. Ross, A First Course in Probability, Pearson Education.
4. W. Feller, An Introduction to Probability Theory and its Applications, Wiley.
5. N.P. Bali and Manish Goyal, A text book of Engineering Mathematics, Laxmi
Publications.
6. B.S. Grewal, Higher Engineering Mathematics, Khanna Publishers.
7. Veerarajan T., Engineering Mathematics (for semester III), Tata McGraw-Hill Publishing
Company Limited.
Course code HSV-102

Course title Human Values and Soft Skills
L T P Credits
Scheme and Credits
2 0 2 3
Class work/Practical 30 Marks
Exam 70 Marks
Total 100 Marks
COURSE OBJECTIVES
1. The course aims at developing the desired English language skills of students of Engineering and
Technology so that they become proficient in communication to excel in their professional lives.
The course has been designed as to enhance their linguistic and communicative competence.
2. Understanding (Clarity) of Human Relationships and Family.
3. Exposure to Issues in Society and nature (larger manmade systems and Nature).
UNIT-I
Motivation and Objectives of Human Values Course, Purpose of Education, Complimentarily of skills
and values, how the current education system falls short, Peers Pressure, Social Pressure In various
dimensions of life, Concept of Competition and Time Management.
UNIT-II
Concept of Preconditioning, Concept of Natural Acceptance in Human Being, Understanding
Relationships, Dealing with anger, Nine universal values in human relationships. Concept of prosperity,
idea of Society, Idea of decentralization of politics, economics, education, justice etc., Its comparison with
centralized systems, Balance in nature.
UNIT-III
Techniques of Good Writing, Writing self-assessment tasks, Precis writing and note making. Paragraph
and Essay writing, Article writing and summarizing
UNIT-IV
Business Communication: Formal and Informal Letter writing, Statement of Purpose, Job application &
CV (summary statement of academic & professional profiles) and Power point presentations through
relevant slides.
English Lab Activity: Blog Writing/Creating a Newsletter, Script writing & enacting for a street play.
Develop negotiating skills by using appropriate language of courtesy, Recording individual efforts and
holding paired interactions and Group Discussions, Preparing and practicing for Interviews.
1. Bhatnagar, Nitin and Mamta Bhatnagar. Communicative English for Engineers and
Professionals. Pearson Education, 2013.
2. Swan, Michael. Practical English Usage. OUP, 1995.
3. Gangal, J.K. Practical Course in Spoken English. New Delhi: PHI Learning, 2015.
4. Konar, Nira. Communication Skills for Professionals. New Delhi: PHI Learning Pvt.
Ltd., 2009.
5. Bansal, R.K. and J.B. Harrison. Spoken English. Orient Longman, 1983.
6. Sharma, Sangeeta and Binod Mishra. Communication Skills for Engineers and
Scientists. Delhi: PHI Learning Pvt. Ltd., 20.
7. Annie Leonard, `` The Story of Stuff,’’ Free Press.
8. Mohandas Karamchand Gandhi,`` The Story of My Experiments with Truth,”
Beacon Press
9. J Krishnamurthy,`` On Education,” Official repository
10. Hermann Hesse ,`` Siddhartha,” Bantam Books.
11. On Education - The Mother Aurobindo Ashram Publication
Course code EEE-101

Course title Basics of Electrical and Electronics Engineering
L T P Credits
Scheme and Credits
3 0 0 3
Class work 30 Marks
Exam 70 Marks
Total 100 Marks
COURSE OBJECTIVES
1. To provide basic knowledge of different elements of electrical and electronics engineering field.
2. To familiarize the students with the concepts of electrical circuits and network Analysis.
3. To understand the basics of AC and DC circuits.
4. To familiarize students to the analysis and design of analog electronic circuits which form the
basic building blocks of almost any electronic system.
5. To introduce p-n junction theory, operation of the semiconductor devices and their use in basic
electronic circuits.
UNIT-I
DC Circuits: Role and importance of circuits in Engineering, Concept of fields, charge, current, voltage, energy
and their interrelationships. Electrical circuit elements (R, L and C), voltage and current sources(ideal &
Controlled),series and parallel circuits, Network reduction: voltage and current division Kirchhoff current and
voltage laws with their applications (Nodal and Mesh Analysis), Source transformation - star delta conversion.
Superposition theorem, Thevenin and Norton Theorems, Millman, Substitution and Reciprocity theorem.
UNIT-II
AC Circuits: Representation of sinusoidal waveforms, average, peak and rms values, complex representation of
impedance, phasor representation, complex power, real power, reactive power, apparent power, power factor and
Energy, Analysis of single-phase ac circuits consisting of R, L, C, RL, RC, RLC combinations (series and
parallel),Resonance; Introduction to three- phase circuits
UNIT-III
Introduction to p-n junction diode and its applications. Half wave & full wave rectifiers. clipping and clamping
circuits, Varactor, Varistor, Voltage Regulator
Bipolar junction transistors and its biasing BJT operation, BJT voltages and currents, CE, CB and CC
characteristics, DC load line and bias point, base bias, emitter feedback bias, collector feedback bias, voltage divider
bias, Thermal stability, biasing BJT switching circuits, transistor power dissipation and switching time, Testing of
bipolar junction transistor with multi-meter, Reading datasheet of BJT.
UNIT-IV
Field Effect Devices: JFET : basic Operation and characteristics, drain and transfer characteristics, pinch off
voltage, parameters of JFET: Transconductance (gm), ac drain resistance (rd), amplification factor(μ) ,Small Signal
Model & Frequency Limitations. MOSFET: basic operation, depletion and enhancement type, pinch-off voltage,
Shockley equation and Small Signal Model of MOSFET, MOS capacitor.
Suggested books:
1. E. Huges, “Electrical Technology”, ELBS.

2. J. Millman and C. Halkias, Integrated Electronics, McGraw Hill, 2ndEdition, 2009.
3. M.M. Mano: Digital Logic Design, Phi.
Suggested reference books:
1. D. P. Kothari and I. J. Nagrath, “Basic Electrical Engineering”, Tata McGraw Hill, 2010.
2. V. Del Toro, “Principles of Electrical engineering”, PHI.
3. Sedra and C. Smith, Microelectronic Circuits: Theory and Applications, Oxford University Press, 6thEdition,
2013.
4. Boylestad and Nashelsky, “Electronic Devices and Circuit Theory” Pearson publishers, 10thEdition
5. R.P. Jain: Modern Digital Electronics, Tmh.
6. Malvino and Leach, ” Digital Principles and Applications”, TMH publishers, 8thEdition
7. Tyagi M.S., “Introduction to Semiconductor Materials and Devices”, John Wiley & Sons, 1993.
8. Basic Electrical Engineering, A.E. Fitzgerald , David Higginbotham 2009 , Arvin Grabel, Tata McGraw-Hill
Publishing Company; 5thEdition.
Course code BSP-101
Course title Physics

L T P Credits
Scheme and Credits
3 1 0 4
Class work 30Marks
Exam 70 Marks
Total 100 Marks
UNIT – I
Review of Atomic Structure and Statistical Mechanics: - Ideas on Atomic Structure, Quantum Mechanics,
The Schrodinger Wave Equation, Statistical Mechanics, Bonding of atoms, Crystalline state. Free electron
theory, Density of states and energy band diagrams, Kronig-Penny model (to introduce origin of band
gap), Energy bands in solids, E-k diagram, Direct and indirect band gaps, Types of electronic materials:
metals, semiconductors, and insulators, Density of states, Occupation probability, Fermi level, Effective
mass, Phonons.
UNIT - II
Elemental and compound semiconductors, Intrinsic and extrinsic semiconductors, Dependence of Fermi
level on carrier-concentration and temperature (equilibrium carrier statistics), Carrier generation and
recombination, Carrier transport: diffusion and drift, The Hall Effect, Einstein Relations, Excess carriers
in semiconductors p-n junction, Excess carriers and Quasi-Fermi Levels, Basic equations for
semiconductor device operation, Solution of carrier transport equation.
UNIT - III
P-N Junctions: - The abrupt junction (Electric field, potential, capacitance), V-I characteristic of an ideal
diode, a real diode. Metal-semiconductor junction (Ohmic and Schottky), Semiconductor materials of
interest for optoelectronic devices. Optical transitions in bulk semiconductors: absorption, spontaneous
emission, and stimulated emission; Joint density of states, Density of states for photons, Transition rates
(Fermi's golden rule), Optical loss and gain; Photovoltaic effect, Exciton, Drude model.
UNIT - IV
Four-point probe and van der Pauw measurements for carrier density, resistivity, and hall mobility; Hot-
point probe measurement, capacitance-voltage measurements, parameter extraction from diode I-V
characteristics, DLTS, band gap by UV-Vis spectroscopy, absorption/transmission.
Densityofstatesin2D, 1D and 0D (qualitatively). Practical examples of low-dimensional systems such as
quantum wells, wires, and dots: design, fabrication, and characterization techniques. Heterojunctions and
associated band- diagram.
1. Pierret, Semiconductor Device Fundamental,

2. P. Bhattacharya, Semiconductor Optoelectronic Devices, Pearson Education
3. J. Singh, Semiconductor Optoelectronics: Physics and Technology, McGraw-HillInc.
4. B.E.A. Saleh and M.C. Teich, Fundamentals of Photonics, John Wiley & Sons, Inc.
5. S. M. Sze, Semiconductor Devices: Physics and Technology, Wiley
6. A. Yariv and P. Yeh, Photonics: Optical Electronics in Modern Communications, Oxford
University Press, New York.
7. Online course: “Semiconductor Optoelectronics” by M R Shenoy on NPTEL
8. Online course: "Optoelectronic Materials and Devices" by Monica Katiyar and Deepak Gupta on
NPTEL
Course code CSE-102
Course title Data Structures Using C
L T P Credits
Scheme and Credits
3 0 0 3
Class work 30 Marks
Exam 70 Marks
Total 100 Marks
UNIT-I
Introduction:
Fundamentals of pointers in C, pointer declaration, passing pointer to functions, pointers and
arrays, dynamic memory allocation, Definition of Algorithm, Data Abstraction, Performance
Analysis & Measurement, Files and related operations inC. Data Structures vs Data Types.
Searching and Sorting Techniques:

Searching techniques: Linear and Binary search, Sorting techniques: Selection, Bubble, Insertion,
Merge sort, Quicksort, List and Table Sorting.
UNIT-II
Linear Data Structures- I
Arrays: Definition of array, Array storage, sparse arrays; Transpose, addition, and multiplication
of sparse matrices, Stacks and Queues and their applications, expression evaluation, A mazing
problem; multiple stacks and queues in an array, Application of stacks recursion polish
expression and their compilation conversion of infix expression to prefix and postfix expression,
Tower of Hanoi problem.
UNIT-III
Linear Data Structures- II
Linked Lists; definition, allocation for stacks and queues. Examples of linked lists, polynomial
addition, comparison of sequential and linked allocation of storage; inversion, concatenation &
copying of the lists. Implementations in C language.
Doubly Linked List: Definition of circular and doubly linked list, header node, insertion and
deletion, sparse matrix, representation using doubly linked lists. Examples for application of
doubly linked lists; dynamic storage management; node structures, routines for allocation and
deallocation, generalized lists and recursive algorithms for copying and comparison of lists.
UNIT-IV
Non Linear Data Structures
Trees, Basic concepts and definitions of a tree and binary tree and associated terminology,
Binary tree traversal techniques, Binary tree representation of trees, transformation of trees into
binary trees, some more operations on binary trees, Binary Search Trees, Heaps and heapsort,
threaded binary trees, Graphs: Representation of graphs and their traversal, Minimum cost
Spanning Trees.
BOOKS:
1. Seymour Lipschutz: Data Structures with C, Schaum’s outline by TMH

2. E Horowitz and S. Sahni: Fundamentals of Data Structures in C, Second
Edition, Universities Press, Hyderabad.
3. R.B. Patel: Expert Data Structures in C, Khanna Publishers,2001.
4. R.L. Kruse: Data Structures & Program Design in C, PHI.
5. D.F. Knuth: The art of Computer Programming Vol 1, Narosa Publications,1985.
6. Byron S. Gottfried & J K Chhabra: Theory and Problems of Programming with C
Language, Schaum Series, TMH,2005.
Course code CSE- 104

Course title Object-Oriented and python programming
L T P Credits
Scheme and Credits
3 0 0 3
Class work 30 Marks
Exam 70 Marks
Total 100 Marks
UNIT-I
The concept of data types; variables, assignments; immutable variables; numerical types; arithmetic
operators and expressions; comments in the program; understanding error messages; Conditions, boolean
logic, logical operators; ranges; Control statements: if-else, loops (for, while); short-circuit (lazy)
evaluation; Strings and text files; manipulating files and directories, os and sys modules; text files:
reading/writing text and numbers from/to a file; creating and reading a formatted file (csv or tabseparated);
String manipulations: subscript operator, indexing, slicing a string.
UNIT-II
Lists, tuples, and dictionaries; basic list operators, replacing, inserting, removing an element; searching
and sorting lists; dictionary literals, adding and removing keys, accessing and replacing values; traversing
dictionaries; Design with functions: hiding redundancy, complexity; arguments and return values; formal
vs actual arguments, named arguments.
UNIT-III
Classes and OOP: classes, objects, attributes and methods; defining classes; design with classes, data
modeling; persistent storage of objects; Encapsulation, Information hiding Method, Signature, Classes
and Instances, Review of Abstraction, inheritance, polymorphism, operator overloading (_eq_, _str_, etc);
abstract classes; exception handling, try block
UNIT-IV
Graphical user interfaces; event-driven programming paradigm; tkinter module, creating simple GUI;
buttons, labels, entry fields, dialogs; widget attributes - sizes, fonts, colors layouts, nested frames.
Reference Books
1. Phillips, Dusty. Python 3 object-oriented programming: Build robust and maintainable software
with object-oriented design patterns in Python 3.8. Packt Publishing Ltd, 2018.
2. Steven F. Lott, Mastering Object-Oriented Python - Second Edition, published by Packt.
3. Python Object Oriented Programming Cookbook, published by Packt.
4. Mark Lutz, Programming Python: Powerful Object-Oriented Programming.
5. Irv Kalb, Object-Oriented Python: Master OOP by Building Games and GUIs Kindle Edition
Course code EEE-101P

Course title Basics of Electrical and Electronics Engineering (P)
L T P Credits
Scheme and Credits
0 0 2 1
Class work 50 Marks
Exam 50 Marks
Total 100 Marks
1. Verify that resistance of conductor is directly proportional to resistivity and length and
inversely proportional to cross- sectional area of the conductor.
2. Verification of Ohm’s Law, Kirchhoff current and voltage laws
3. Verification of temperature co-efficient of resistance: (i) Positive for Tungsten and
Nichrome and (ii) Negative for carbon.
4. To measure DC voltage and current, AC voltage and current with multi-meter
5. To observe waveforms on oscilloscope, measure basic parameters amplitude and
frequency of sine wave and square wave.
6. Obtain VI characteristics of semiconductor rectifier diode, LED, Photo-diode
7. To observe waveform at the output of half wave rectifier with and without filter
capacitor.
8. To observe waveform at the output of full wave rectifier with and without filter capacitor.
9. To experimentally plot the input and output characteristics of a given BJT transistor in
CE configuration and calculate its various parameters.
10. To experimentally plot the input and output characteristics of a given BJT transistor in
CB configuration and calculate its various parameters.
11. To study the transfer and drain characteristics of JFET and calculate its various
parameters.
12. To study the transfer and drain characteristics of MOSFET and calculate its various
parameters.
Course code BSP-101P

Course title Physics (P)

L T P Credits
Scheme and Credits
0 0 2 1
Class work 50 Marks
Exam 50 Marks
Total 100 Marks
1. To study the forward and reverse characteristics of P-N junction diode.

2. To study the characteristics of Solar cell and find out the fill factor..
3. To study the reverse characteristics of Zener diode and voltage regulation using Zener Diode.
4. To determine Planks constant using photocell.
5. To measure e/m of electron using helical method.
6. To find capacitance of condenser using fleshing and quenching experiment.
7. To find temperature co-efficient of platinum using Callender Griffith bridge.
8. To find out low resistance by Carry Foster bridge.
9. To find resistance of galvanometer by post office box.
10. To measure resistance using four probe methode.
11. To compare the capacitance of two capacitors using De‘Sauty Bridge.
Course title Data Structures Using C (P)
L T P Credits
Scheme and Credits
0 0 2 1
Class work 50 Marks
Exam 50 Marks
Total 100 Marks
1. Write a program to search an element in a two-dimensional array using linear search.

2. Using iteration & recursion concepts write programs for finding the element in the array using Binary
Search Method
3. Write a program to perform following operations on tables using functions only
(a) Addition (b) Subtraction (c) Multiplication (d) Transpose
4. Using iteration & recursion concepts write the programs for Quick Sort Technique
5. Write a program to implement the various operations on string such as length of string concatenation,
reverse of a string & copy of a string to another.
6. Write a program for swapping of two numbers using ‘call by value’ and ‘call by reference strategies.
7. Write a program to implement binary search tree.
8. (Insertion and Deletion in Binary search Tree)
9. Write a program to create a linked list & perform operations such as insert, delete, update, reverse in
the link list
10. Write the program for implementation of a file and performing operations such as insert, delete,
update a record in the file.
11. Create a linked list and perform the following operations on it
(a) add a node (b) Delete a node
Course title Object Oriented Concepts and Python Programming (P)
L T P Credits
Scheme and Credits
0 0 2 1
Class work 50Marks
Exam 50 Marks
Total 100 Marks
1. Basic building blocks of a Python program (variables, conditional statements, loops, libraries,
functions, errors).
2. Data structures (trees, dictionaries, tuples)
3. Object Oriented programming (classes, objects, inheritance, polymorphism, abstract classes).
4. PyQt for creating graphical user interfaces for interactive programs
5. NumPy (Matrices, vectors, linear algebra)
6. SciPy (Package for numerical computations)
7. Matplotlib (Plotting)
8. Interactive Python (IPython)
Course code MEE-102P
Course title Workshop Practices (P)
L T P Credits
Scheme and Credits
1 0 3 2.5
Class work 50 Marks
Exam 50 Marks
Total 100 Marks
COURSE OBJECTIVES
1. To impart fundamental Knowledge of engineering practices such as fitting, wood working,

foundry, machining, welding, etc. for manufacturing a product.
2. To prepare the students to understand the various tools and equipment’s used in these processes
and their working principle
3. To impart fundamental Knowledge of Lathe machine
4. To able to understand the basic knowledge of various welding processes
Class Work
Introduction:
Introduction to Manufacturing Processes and their Classification, Introduction to additive manufacturing,
Industrial Safety.
Machining Shop
Lathe, description of lathe: headstock, tailstock, gearbox, carriage, apron, cutting speed, feed & depth of
cut, cutting tools, Chucks: 3 jaw, 4 jaw.
Fitting shop:
Introduction, classification of metals: ferrous and nonferrous, fitting tools: measuring and marking tools,
marking schemes for a fitting jobs, cutting tools.
Carpentry shop:
Introduction of carpentry, types of woods, carpentry tolls: measuring tools, marking tolls, cutting tools:
saws, chisels, planning tools, drilling tools, striking tools, drilling tools, wood working joints, wood
working lathe.
Foundry Shop
Introduction, foundry hand tools, measuring boxes, ladle, moulding, furnaces,Pattern: Types of Pattern
and Allowances
Welding Shop
Introduction to welding, Classification of Welding Processes,Arc welding & Gas welding equipment’s.
Reference Books:
7. S K Hajra Choudhury, Nirjhar Roy, A K Hajra Choudhury, Elements of workshop Technology (vol.
1&2), Media Promoters.
8. B S Raghuwanshi, A Course in Workshop Technology (manufacturing Process vol. 1& 2) Dhanpat
Rai & CO.
9. O.P. Khanna, Workshop Technology. Dhanpat Rai Publication.
10. W A J Chapman, Workshop technology in SI unit (part – 1 &2), Mc Graw Hill Education.
11. M.P. GROOVER, Principles of Modern Manufacturing, Wiley.
12. Kalpakjian, Manufacturing Process for Engineering Materials, Pearson Education India.
Lab Work
List of Experiments
1. To study different types of measuring tools used in metrology and determine least counts of
vernier callipers, micrometres and vernier height gauges.
2. To study different types of machine tools (lathe, shaper, planer, milling, drilling machines)
3. To prepare a job on a lathe involving like facing, outside turning, taper turning, step turning,
radius making and parting-off.
4. To study different types of fitting tools and marking tools used in fitting practice.
5. To prepare a job made out of MS Flats, making saw – cut filling V-cut taper at the corners.
6. To prepare lay out on a metal sheet by making and prepare rectangular tray pipe shaped
components e.g. funnel.
7. To prepare joints for welding suitable for butt welding and lap welding.
8. To study various types of carpentry tools and prepare simple types of at least two wooden joints.
9. To prepare simple engineering components/shapes by forging.
10. To prepare mold and core assembly.
11. To prepare horizontal surface/vertical surface/curved surface/slats or V-grooves on a
shaper/planner.
12. To prepare a job involving side and face milling on a milling
13. To prepare a job on CNC Machine/Additive Manufacturing.
Note : At least eight experiments/jobs are to be performed/prepared by the students in the semester.
Coursetitle Engineering Graphics (Web Designing)
L T P Credits
Scheme and Credits
1 0 2 2
Class work 50 Marks
Exam 50 Marks
Total 100 Marks
Class work
Brief history of Internet, introduction to world wide web, basic principles involved in developing a web
site, rules of web designing, web standards, audience requirements, Design concept.
Introduction to elements of HTML, XHTML and CSS.
Javascript as programming language, Language Syntax: Data types, Values, Variables, Expressions and
Operators. JavaScript Statements, loops, arrays, strings, methods, Defining and Invoking functions and
their closure.
Introduction of Google Web Designer, Firefox, Wordpress, sublime text, Angular.JS, jQuery etc.
Lab work
1. Prepare a survey document of ten website which you like and dislike with various reasons.
(Prerequisite)
2. Introduction to basic HTML elements
3. Use table tag to format web page. Also create the Time Table of your class using table tag.
4. Create your profile page i.e. educational details, Hobbies, Achievement, My Ideals etc.
5. Create Style sheet to set formatting for text tags and embed that style sheet on web pages created for
your site.
6. Design a web page and embed various multimedia features in the page.
7. Design signup form to validate username, password, and phone numbers etc using Java script.
8. Write a JavaScript program to determine whether a given year is a leap year in the Gregorian calendar.
9. Write a JavaScript program to convert temperatures to and from celsius, Fahrenheit.
10. Installation of Wordpress and designing the wordpress site.
11. Introduction to Dreamweaver and setting up site using Dreamweaver.
12. Submission of Website with Report.
3
rd
SEMESTER
(Cyber Security)
Semester – III
Session Examination
L T P al
1 ESC Digital Electronics 3 0 0 3 30 70 100
2 PCC Introduction to 3 0 0 3 30 70 100

3 BSC Discrete 3 0 0 3 30 70 100
Mathematics
4 ESC R Programming 3 0 0 3 30 70 100
5 PCC Operating 3 0 0 3 30 70 100

Systems
6 LC Digital Electronics 0 0 2 1 50 50 100
(P)
7 LC Introduction to 0 0 2 1 50 50 100
(P)
8 LC R Programming (P) 0 0 2 1 50 50 100
9 LC Operating Systems (P) 0 0 2 1 50 50 100
10 BSC Aptitude Reasoning- I 3 0 0 3 30 70 100
Total 18 0 8 22 1000
DIGITAL ELECTRONICS
Semester III
Course code
Category Engineering Science courses
Course title Digital Electronics
Scheme and Credits L T P Credits
3 0 0 3
Classwork 30 Marks
Exam 70 Marks
Total 100 Marks
Note: The examiner will set nine questions in total. Question one will be compulsory. Question one will
have seven parts of 2 marks each from all units, and the remaining eight questions of 14 marks each to be
set by taking two questions from each unit. The students have to attempt five questions in total, the first
being compulsory and selecting one from each unit.
COURSE OBJECTIVES:
1. To understand the basic theoretical concepts of digital systems like the binary system and
Boolean algebra.
2. To use Boolean algebraic formulations to design digital systems. To design using
combinational/sequential circuits.
3. To express real-life problems in logic design terminology.
4. To understand the logic of adders, subtractors and converters.
COURSE OUTCOMES:
At the end of this course, students will demonstrate the ability to
CO1: Outline the general concepts and terminology related to logic gates, logic families,
combinational and sequential circuits.
CO2: Discuss the basic analog/digital components and their interconnections in logic families and
circuits.
CO3: Apply different methods/techniques to design various digital circuits.
CO4: Analyze day to day problems and industrial problems for their solutions using digital circuits.
CO5: Contrast different types of digital circuits and their designing methods.
CO6: Design digital circuit for various practical problems.
UNIT – I
FUNDAMENTALS OF DIGITAL SYSTEMS AND LOGIC FAMILIES
Digital signals, digital circuits, AND, OR, NOT, NAND, NOR and Exclusive-OR operations, Boolean
algebra, examples of IC gates, number systems - binary, signed binary, octal hexadecimal number, binary
arithmetic, one’s and two’s complements arithmetic, codes, error detecting and correcting codes.
UNIT - II
COMBINATIONAL DIGITAL CIRCUITS
Standard representation for logic functions, K-map representation, and simplification of logic functions
using K-map, minimization of logical functions. Don’t care conditions, Multiplexer, De- Multiplexer,
Decoders, Adders, Subtractors, BCD arithmetic, carry look-ahead adder, serial adder, ALU, elementary
ALU design, popular MSI chips, digital comparator, parity checker/generator, code converters, priority
encoders, decoders/drivers for display devices, Q-M method of function realization.
UNIT – III
SEQUENTIAL CIRCUITS AND SYSTEMS
A 1-bit memory, the circuit properties of the Bistable latch, the clocked SR flip-flop, J-K flip-flop, T
flip-flop and D flip-flop, applications of flip-flops, shift registers, applications of shift registers, serial-to-
parallel converter, parallel-to-serial converter, ring counter, sequence generator, ripple
(Asynchronous) counters, synchronous counters, counters design using flip-flops, special counter IC’s,
asynchronous sequential counters, applications of counters.
UNIT – IV
A/D AND D/A CONVERTERS
Digital to analog converters: weighted resistor/converter, R-2-R Ladder D/A converter, specifications for
D/A converters, examples of D/A converter ICs, sample and hold circuit, Analog to digital converters:
quantization and encoding, parallel comparator A/D converter, successive approximation A/D converter,
counting A/D converter, dual slope A/D converter.
TEXT AND REFERENCE BOOKS:
1. R. P. Jain, "Modern Digital Electronics", McGraw Hill Education, 2009
2. M. M. Mano, "Digital logic and Computer Design", Pearson Education India,2016
3. A. Kumar, "Fundamentals of Digital Circuits", Prentice Hall India, 2016
4. Nasib Singh Gill and J B Dixit, “Digital Design and Computer Organization”, University
Science Press, New Delhi
DISCRETE MATHEMATICS
Semester III
Course code
Category Basic Science courses
Course title Discrete Mathematics
3 0 0 3
Classwork 30 Marks
Exam 70 Marks
Total 100 Marks
COURSE OBJECTIVES:
1. To understand the basic theoretical concepts of set theory, functions, and relations.
2. To understand the basic theoretical concepts of logic systems and Boolean algebra.
3. To express real-life problem of basic counting techniques and recurrence relations, algebraic
structures.
4. The use of graphs theory concepts in real-life examples
COURSE OUTCOMES:
CO1: To solve mathematical problems based on concepts of set theory, relations, functions and
lattices.
CO2: To express logical sentences in terms of quantifiers and logical connectives.
CO3: To apply basic counting techniques to solve permutation and combination problems.
CO4: To solve recurrence relations.
CO5: To classify the algebraic structure of any given mathematical problem.
CO6: To evaluate Boolean functions and simplify expressions using the properties of Boolean
algebra
CO7: To develop the given problem as graph networks and solve it with techniques of graph
theory.
UNIT - I
SET THEORY, RELATIONS, FUNCTIONS, LOGIC AND PROPOSITIONAL CALCULUS
Set Theory: Introduction to set theory, Venn diagrams, Set operations, Algebra of sets, Duality, Finite and
infinite sets, Counting principles, Power sets, Partitions, and Multi sets.
Relations: Cartesian product, Representation of relations, Types of relation, Binary relation, Equivalence
relations, Partitions, Partial ordering relations, POSET, Hasse diagram, Lattices and its types.
Functions: Definition, Types of functions, Bijective functions, Composition of functions, Inverse
functions, recursively defined functions, Finite and infinite sets, Countable and uncountable sets, Cantor's
diagonal argument and The Power Set theorem, Schroeder-Bernstein theorem.
Logic And Propositional Calculus: Introduction, Propositions and compound propositions, Logical
operations, Propositions and truth tables, Tautologies, Contradictions, Logical equivalence, Algebra of
propositions, Conditional and Bi-conditional statements, The use of Quantifiers.
UNIT - II
BASIC COUNTING TECHNIQUES AND RECURRENCE RELATION
Basic Counting Techniques: Pigeon-hole principle, Permutation and Combination, the Division
algorithm: Prime Numbers, The GCD: Euclidean Algorithm, The Fundamental Theorem of Arithmetic.
Recursion And Recurrence Relation: Polynomials and their evaluation, Sequences, Introduction to
AP, GP and AG Series, Partial Fractions, Recurrence Relation, Linear Recurrence Relations with Constant
Coefficients, Linear Homogeneous Recurrence Relations with Constant Coefficients, Particular Solution-
Homogeneous Linear Difference Equations, Non-Homogeneous Linear Difference Equations, Total
Solution, solving recurrence relation using generating functions.
UNIT - III
ALGEBRAIC STRUCTURES
Definitions and examples of Algebraic Structures with one Binary Operation: Semi Groups, Monoids,
Groups, Semigroups, Subgroups, Abelian groups, Cosets, Normal Subgroup, Cyclic groups, Congruence
Relation and Quotient Structures, Permutation Groups, Lagrange’s Theorem, Homomorphism,
Isomorphism, Automorphism.
Definitions and examples of Algebraic Structures with two Binary Operation: Rings, Integral
Domain, Fields; Boolean Algebra and Boolean Ring, Identities of Boolean Algebra, Duality,
Representation of Boolean Function, Disjunctive and Conjunctive Normal Form
UNIT - IV
GRAPHS THEORY: Introduction to graphs and their properties, Degree, Connectivity, Path, Cycle,
Directed and undirected graphs, Subgraph, Bipartite Graphs, Regular Graphs, Connected Graphs,
Multigraph and Weighted graph, Homomorphic and Isomorphic graphs, cut points and bridges, Paths and
circuits, shortest path algorithm for weighted graphs, Eulerian paths and circuits, Hamiltonian path and
circuits, Planar Graphs, Euler’s formulae, Graph Colouring.
1. Kenneth H. Rosen, Discrete Mathematics and its Applications, 6th Edition, Tata McGraw Hill,
2011.
2. Satinder Bal Gupta: A Text Book of Discrete Mathematics and Structures, University Science
Press, Delhi.
3. C. L. Liu and D. P. Mohapatra, Elements of Discrete Mathematics A Computer Oriented
Approach, Tata McGraw Hill, 3rd Edition, 2008.
4. J.P. Trembley and R. Manohar, Discrete Mathematical Structures with Applications to
Computer Science, Tata McGraw Hill – 13th reprint, 2012.
5. Richard Johnsonbaugh, Discrete Mathematics, 6th Edition, Pearson Education Asia, 2011.
6. S. Lipschutz and M. Lipson, Discrete Mathematics, Tata McGraw Hill, 3rd Edition, 2010.
7. B. Kolman, R. C. Busby and S. C. Ross, Discrete Mathematical structures, 6th Edition, PHI,
2010.
INTRODUCTION TO INFORMATION SECURITY
Semester III
Course code
Category Professional Core course
Course title Introduction to Information Security
3 0 0 3
Classwork 30 Marks
Exam 70 Marks
Total 100 Marks
have seven parts of 2 marks each from all units, and the remaining eight questions of 14 marks each to
be set by taking two questions from each unit. The students have to attempt five questions in total, the
first being compulsory and selecting one from each unit.
COURSE OBJECTIVES:
1. Learning the basics and need of information security
2. Understanding moral and ethics of cyber security
3. Applying user authentication principles and access controls
COURSE OUTCOMES:
CO1: Understand the fundamentals of Information Security and Infrastructure
CO2: Illustrate and apply morals and ethics of cyber security
CO3: Interpret the concepts of cyber security in real-life
CO4: Understand different types of attacks and their applications
CO5: Study different access controls in cyber security
UNIT – I
INFORMATION SECURITY BASICS
What is Information Security, Goals of Information Security: Integrity Models, Availability Models, and
Security is not just VAPT, Security Models: Security Model Work, Confidentiality, Integrity, and
Availability (CIA) Triad, Real World Examples, Examples of Breach Incidents
UNIT – II
DOMAINS OF CYBER SECURITY
Domains of Cyber Security, Morals and Ethics, Cyber Law and Cyber Security: IT Act 2000 and
Amendments, Social Engineering, Cyber Stalking, Botnets Attack Vector, Risk Analysis: Threat Vectors,
Threat Sources and Targets, Types of Attacks: Malicious Mobile code, Advanced Persistent Threats
(APTs), Manual Attacks
UNIT – III
USER AUTHENTICATION
Electronic User Authentication Principles, Password-Based Authentication, Token-Based
Authentication, Biometric based Authentication, Remote User Authentication, Security issues for user
authentication, Practical Applications (Iris biometric System), Case Study (Security Problems for ATM
Systems)
UNIT – IV
ACCESS CONTROLS
Access Control: Access Control Principles, Subjects, Objects and access Rights, Discretionary Access
Control (DAC), Mandatory Access Control (MAC), Role-based Access Control (RBAC), Attribute based
Access Control, Identity, Credential and Access Management, Trust Frameworks, Case Studies
1. Information Security: The Complete Reference by Mark Rhodes-Ousley
2. Computer Networking with Internet Protocols and Technology by William Stallings
3. Getting an Information Security Job for Dummies by Peter H. Gregory
Help Pages:
1. Breaking into InfoSec: A beginner's guide to all things Cyber Security
Web Sites:
1. VMware: https://www.vmware.com/in.html
2. VirtualBox: https://www.virtualbox.org/
3. Kali: https://www.kali.org/downloads/ Web Tutorials
4. SANS: https://www.sans.org/information-security/
5. Geeksforgeeks: https://www.geeksforgeeks.org/what-is-information-security/
R PROGRAMMING
Semester III
Course code
Course title R Programming
3 0 0 3
Classwork 30 Marks
Exam 70 Marks
Total 100 Marks
COURSE OBJECTIVES:
1. Understand the basics of R and different data types
2. Application of different operators and control statements
3. Analyzing data and understanding different statistics using R
COURSE OUTCOMES:
CO1. Learn Fundamentals of R.
CO2. Covers how to use different functions in R, how to read data into R, accessing R packages, writing,
R functions, debugging, and organizing data using R functions.
CO3. Cover the Basics of statistical data analysis with examples.
CO4. To apply mathematical and statistical operations data structures in R
CO5. To explain critical R programming language concepts such as control structures and recursion
CO6. To demonstrate and implement basic R programming framework and data structures
UNIT – I
BASICS OF R
Introduction to R: What is R? – Why R? – Advantages of R over Other Programming Languages- R
Studio: R command Prompt, R script file, comments.
Handling Packages in R: Installing a R Package, Few commands to get started: installed. packages(),
package. Description(), help(), find. Package(), library() - Input and Output – Entering Data from
keyboard.
R - Data Types: Vectors, Lists, Matrices, Arrays, Factors, Data Frame.
R - Variables: Variable assignment, Data types of Variable, Finding Variable ls(), Deleting Variables
UNIT – II
OPERATORS AND LOOPS
R - Operators: Arithmetic Operators, Relational Operators, Logical Operator, Assignment Operators,
Miscellaneous Operators.
R - Decision Making: if statement, if – else statement, if – else if statement, switch statement.
R - Loops: repeat loop, while loop, for loop - Loop control statement: break statement, next statement.
R - Function: function definition, Built-inn functions: mean(), paste(), sum(), min(), max(), seq(), user-
defined function, calling a function, calling a function without an argument, calling a function with
argument values.
UNIT – III
DATA TYPES IN R
R – Strings: Manipulating Text in Data: substr(), strsplit(), paste(), grep(), toupper(), tolower().
R – Vectors: Sequence vector, rep function, vector access, vector names, vector math, vector
recycling, vector element sorting.
R – List: Creating a List, List Tags and Values, Add/Delete Element to or from a List, Size of List,
Merging Lists, Converting List to Vector.
R – Matrices: Accessing Elements of a Matrix, Matrix Computations: Addition, subtraction,
Multiplication and Division.
R - Arrays: Naming Columns and Rows, Accessing Array Elements, Manipulating Array Elements,
Calculation Across Array Elements.
R – Factors: creating factors, generating factor levels gl().
R - Data Frames: Create Data Frame, Data Frame Access, Understanding Data in Data Frames: dim(),
nrow(), ncol(), str(), Summary(), names(), head(), tail(), edit() functions - Extract Data from Data Frame,
Expand Data Frame: Add Column, Add Row - Joining columns and rows in a Data frame rbind() and
cbind() – Merging Data frames merge() – Melting and Casting data melt(), cast().
UNIT -IV
DATA VISUALIZATION
Loading and handling Data in R: Getting and Setting the Working Directory – getwd(), setwd(), dir()
- R-CSV Files - Input as a CSV file, Reading a CSV File, Analyzing the CSV File: summary(), min(),
max(), range(), mean(), median(), apply() - Writing into a CSV File – R -Excel File – Reading the Excel
file.
Data Visualization through various plots and charts: bar charts, histogram, frequency polygon,
density plots, scatter plots, box & whisker plots, heat and contour plots, plotting the above graphs in R,
plotting with package ggplot2.
TEXT AND REFERENCE BOOKS

1. W. N. Venables, D. M. Smith and the R core Team, An introduction to R, Notes on R: A
Programming Environment for Data Analysis and Graphics, version 3.3.2, 2016.
2. Saroj Dahiya Ratnoo and Himmat Singh Ratnoo, Essentials of R for Data Analytics, Wiley,
2021.
3. Hadley Wickham and Garrett Grolemund, R for Data Science Import, Tidy, Transform and
model Data, O’Reilly, 2017.
4. Paul Teeter, R Cookbook, O’Reilly, 2011.
5. Gareth James, Daniela Witten, Trevor Hastie, Robert Tibshirani, An Introduction to Statistical
Learning with Applications in R, Springer, 2013.
6. Han, J., Kamber, M, Pei, J., Data Mining Concepts and Techniques, Third edition, Morgan
Kaufmann, 2012.
OPERATING SYSTEMS
Semester III
Course code
Course title Operating Systems
3 0 0 3
Classwork 30 Marks
Exam 70 Marks
Total 100 Marks
COURSE OBJECTIVES:
1. To learn the importance of operating system for Computer System.
2. To make aware of different types of Operating System and their services.
3. To learn different process scheduling algorithms and synchronization techniques to achieve better
performance of a computer system.
4. To know virtual memory concepts.
5. To learn secondary memory management.
COURSE OUTCOMES:
CO1. Understand the structure and architectural components of OS to analyze and design the
applications to run in parallel. Moreover, students would be able to develop scheduling algorithms
to optimize various parameters like CPU utilization, Throughput, Turnaround Time, Waiting
Time, Response Time for research purpose.
CO2. Understand the design issues associated with Operating system (e.g. Mutual exclusion, Deadlock
detection etc.) to gain insight towards developing algorithms/techniques for efficient deadlock
handling.
CO3. For a given specification of memory organization, develop the techniques for optimally allocating
memory to processes by increasing memory utilization and for improving the access time.
CO4. Design and implement file management system for a given specification.
CO5. Identify, use and evaluate the disk management policies with respect to various performance
evaluation parameters.
UNIT- I
INTRODUCTION: Concept of Operating Systems, Generations of Operating systems, Types of Operating
Systems, OS Services.
PROCESSES: Definition, Process Relationship, Different states of a Process, Process State transitions,
Process Control Block (PCB), Context switching. Thread: Definition, Various states, Benefits of threads,
Types of threads, Multithreading.
PROCESS SCHEDULING: Foundation and Scheduling objectives, Types of Schedulers, Scheduling
criteria: CPU utilization, Throughput, Turnaround Time, Waiting Time, Response Time; Scheduling
algorithms: Preemptive and Non-pre-emptive, FCFS, SJF, SRTF, RR Scheduling.
UNIT – II
INTER-PROCESS COMMUNICATION: Critical Section, Race Conditions, Mutual Exclusion, The
Producer/Consumer Problem, Semaphores, Event Counters, Monitors, Message Passing, Classical IPC
Problems: Reader’s & Writer Problem, Dinning Philosopher Problem etc.
DEADLOCKS: Definition, Necessary and sufficient conditions for Deadlock, Deadlock Prevention, and
Deadlock Avoidance: Banker’s algorithm, Deadlock detection and Recovery.
UNIT- III
MEMORY MANAGEMENT: Basic concept, Logical and Physical address map, Memory allocation:
Contiguous Memory allocation – Fixed and variable partition–Internal and External fragmentation and
Compaction; Paging: Principle of operation – Page allocation – Hardware support for paging, Protection
and sharing, Disadvantages of paging.
VIRTUAL MEMORY: Basics of Virtual Memory – Hardware and control structures –Locality of
reference, Page fault, Working Set, Dirty page/Dirty bit – Demand paging, Page Replacement algorithms:
Optimal, First in First Out (FIFO), Optimal Page Replacement and Least Recently used (LRU).
UNIT-IV
FILE MANAGEMENT: Concept of File, Access methods, File types, File operation, Directory structure,
File System structure, Allocation methods (contiguous, linked, indexed), efficiency and performance.
DISK MANAGEMENT: Disk structure, Disk scheduling - FCFS, SSTF, SCAN, C-SCAN, Disk
reliability, Disk formatting, Boot-block, Bad blocks.
Case study on UNIX and WINDOWS Operating System.

1. Operating System Concepts Essentials, 9th Edition by Avi Silberschatz,
2. Peter Galvin, Greg Gagne, Wiley Asia Student Edition.
3. Operating Systems: Internals and Design Principles, 5th Edition, William Stallings, Prentice Hall of
India.
4. Operating System: A Design-oriented Approach, 1st Edition by Charles Crowley, Irwin Publishing
5. Operating Systems: A Modern Perspective, 2nd Edition by Gary J. Nutt, Addison-Wesle
6. Design of the Unix Operating Systems, 8th Edition by Maurice Bach, Prentice-Hall of India
7. Understanding the Linux Kernel, 3rd Edition, Daniel P. Bovet, Marco Cesati, O'Reilly and Associates.
DIGITAL ELECTRONICS LAB
Semester III
Course code
Category Engineering Science courses
Course title Digital Electronics Lab
0 0 2 1
Classwork 50 Marks
Exam 50 Marks
Total 100 Marks
COURSE OUTCOMES:
CO1. Implement the basic digital theory concepts practically and will be able to verify various
results derived in theory.
CO2. Design, analyze and troubleshoot broad range of combinational and sequential circuits for
various practical problems using basic gates and flip flops I.C’s.
CO3. Develop technical writing skills to communication effectively and present one’s own work.
CO4. Acquire teamwork skills for finding sustainable solution of a complex problem and working
effectively in groups
EXPERIMENTS
Implementation of all experiments with the help of Bread-Board.
1. Study of Logic Gates: Truth-table verification of OR, AND, NOT, XOR, NAND and NOR
gates; Realization of OR, AND, NOT and XOR functions using universal gates.
2. Half Adder / Full Adder: Realization using basic and XOR gates.
3. Half Subtractor / Full Subtractor: Realization using NAND gates.
4. 4-Bit Binary-to-Gray & Gray-to-Binary Code Converter: Realization using XOR gates.
5. 4-Bit and 8-Bit Comparator: Implementation using IC7485 magnitude comparator chips.
6. Multiplexer: Truth-table verification and realization of Half adder and Full adder.
7. Demultiplexer: Truth-table verification and realization of Half subtractor and Full subtractor.
8. Flip Flops: Truth-table verification of JK Master Slave FF, T-type and D-type FF.
9. Asynchronous Counter: Realization of 4-bit up counter and Mod-N counter.
10. Synchronous Counter: Realization of 4-bit up/down counter and Mod-N counter.
11. Shift Register: Study of shift right, SIPO, SISO, PIPO, PISO & Shift left operations.
12. DAC Operation: Study of 8-bit DAC, obtain staircase waveform.
13. ADC Operations: Study of 8-bit ADC
INTRODUCTION TO INFORMATION SECURITY LAB
Semester III
Course code
Category Lab courses
Course title Information Security Lab
0 0 2 1
Classwork 50 Marks
Exam 50 Marks
Total 100 Marks
COURSE OUTCOMES:
CO1. At the end of this course, students will demonstrate the ability to
CO2. Apply commands of UNIX to perform different operations.
CO3. Install different operating systems by using Virtual Box or other type.
CO4. Apply different concepts of information security
CO5. Acquire teamwork skills for investigating case studies and its application on other real-life
problems.
CO6. Analyze different ways of security measures for securing data, documents, passwords.
EXPERIMENTS
1. Installation of Different types of OS file installation: Linux, Windows (ova/ovf/iso image)
2. Study different real case studies on Confidentiality (Encryption, Steganography)
3. Case studies on Integrity (Hash, Checksum etc.), Availability (Backups)
4. Various Case Studies on Cyber Crimes and IT Act.
5. Study of steps to protect your personal computer system by creating User Accounts with
Passwords and types of User Accounts for safety and security.
6. Study the steps to protect a Microsoft Word Document of different version with different
operating system.
7. Study the steps to remove Passwords from Microsoft Word
8. Study various methods of protecting and securing databases.
9. Study “How to make strong passwords” and “passwords cracking techniques”.
10. Study the steps to hack a strong password.
R PROGRAMMING LAB
Semester III
Course code
Course title R Programming Lab
0 0 2 1
Classwork 50 Marks
Exam 50 Marks
Total 100 Marks
COURSE OBJECTIVES:
The objective of R programming lab is to cover:
1. The basics of statistical computing and data analysis
2. How to use R for analytical programming
3. How to implement data structure in R
4. R loop functions and debugging tools
5. Writing custom R functions
COURSE OUTCOMES:
CO1: Understanding the types, classes and functions of R Programming.
CO2: Accessing and Processing of Data.
CO3: Understanding the I/O interface programming.
CO4: Study and Analyse Data Visualisation.
CO5: Implement any application level simulation using R.
EXPERIMENTS
1. Write a R program to take input from the user (name and age) and display the values.
2. Write a R program to get the details of the objects in memory.
3. Creating a sequence of numbers from 20 to 50 and find the mean of numbers from 20 to 60 and sum
of numbers from 51 to 91.
4. Creating a simple bar plot of five subjects marks.
5. Get the unique elements of a string and unique numbers of vectors
6. Appending value to a given empty vector
7. Multiplying two vectors of integer type and length 3
8. Find the sum, mean and product of a vector, ignoring elements like NA and NaN.
9. To create three vectors a,b,c with 3 integers. Combine three vectors to become a 3*3 matrix where
each column represents a vector. Print the content of the matrix
10. Program to create a matrix from a list of given vectors
OPERATING SYSTEMS LAB
Semester III
Course code
Course title Operating Systems Lab
0 0 2 1
Classwork 50 Marks
Exam 50 Marks
Total 100 Marks
COURSE OBJECTIVES:
1. To introduce Basic Unix general purpose Commands
2. To learn network Unix commands.
3. To learn shell script
4. To learn different programming language in Unix editor environment and implement
different Operating system algorithm
5. To learn about file management and different types of permission setup.
6. To understand how system processes work and how to manage them
COURSE OUTCOMES:
CO1. Experiment with Unix commands and shell programming.
CO2. Able to build shell program for process and file system management with system calls.
CO3. Able to implement and analyse the performance of different algorithm of Operating Systems like
CPU scheduling algorithm,
CO4. Able to implement and analyse the performance of different algorithm of page replacement
algorithms, deadlock avoidance, detection algorithm and so on.
CO5. Able to design and develop a course project that can have positive impact on environment or society
or mankind.
EXPERIMENTS
1. Basics of UNIX
2. UNIX commands
3. Implementation of FCFS and SJF CPU scheduling algorithms
4. Implementation of Round Robin and Priority CPU Scheduling
5. Implementation of Producer-Consumer problem using semaphores
6. Implementation of Dining Philosphers Problem
7. Implementation of FIFO Page Replacement Algorithms
8. Implementation of LRU Page Replacement Algorithms
9. Implementation of Sequential File Allocation Strategies
10. Implementation of Indexed File Allocation Strategies
APTITUDE REASONING -I
Semester III
Course code
Category BSC
Course title Aptitude Reasoning- I
Scheme and L T P Credits
Credits 3 0 0 3
Class work 30 Marks
Exam 70 Marks
Total 100 Marks
COURSE OBJECTIVES:
This course is designed to suit the need of the outgoing students and to acquaint them with frequently
asked patterns in quantitative aptitude and logical reasoning during various examinations and campus
interviews.
COURSE OUTCOMES:
On successful completion of the course the students will be able to:
CO1. Understand the basic concepts of quantitative ability
CO2. Understand the basic concepts of logical reasoning Skills
CO3. Acquire satisfactory competency in use of reasoning
CO4. Solve campus placements aptitude papers covering Quantitative Ability, Logical Reasoning
Ability
CO5. Compete in various competitive exams like CAT, CMAT, GATE, GRE, GATE, UPSC, GPSC
etc.
UNIT – I
Quantitative Ability (Basic Mathematics). Number Systems, LCM and HCF , Decimal Fractions,
Simplification, Square Roots and Cube Roots, Discount
UNIT – II
Quantitative Ability (Applied & Engineering Mathematics Profit and Loss, Simple and Compound
Interest, Time, Speed and Distance, Area, Height and Distance
UNIT – III
Data Interpretation. Data Interpretation, Tables, Column Graphs, Bar Graphs, Line Charts
UNIT – IV
Logical Reasoning (Deductive Reasoning): Analogy, Blood Relation, Directional Sense, Number and
Letter Series, Clocks,

1. A Modern Approach To Verbal & Non Verbal Reasoning By R S Agarwal
2. Analytical and Logical reasoning By Sijwali B S
3. Quantitative aptitude for Competitive examination By R S Agarwal
4. Analytical and Logical reasoning for CAT and other management entrance test By Sijwali B S
5. Quantitative Aptitude by Competitive Examinations by Abhijit Guha 4 th edition
4th
SEMESTER
(Cyber Security)
Semester – IV
L T P al
1 BSC Aptitude Reasoning -II 3 0 0 3 30 70 100
2 PCC Computer Architecture 3 0 0 3 30 70 100
and Organization
3 PCC Analysis and Design 3 0 0 3 30 70 100
of Algorithms
4 PCC AI Data Analytics 3 0 0 3 30 70 100
using R
5 PCC Cryptography and 3 0 0 3 30 70 100
Security
6 PCC Soft Computing 3 0 0 3 30 70 100
7 LC Cryptography and 0 0 2 1 50 50 100
Security Lab (P)
8 LC Analysis and Design of 0 0 2 1 50 50 100
Algorithms Lab (P)
9 LC AI Data Analytics using 0 0 2 1 50 50 100
R Lab (P)
10 AU Indian Constitution* 2 0 0 0 Refer Note
Total 21 0 6 24 900
*NOTE: The examination of the regular students will be conducted by the concerned college/Institute
internally. Each student will be required to score a minimum of 40% marks to qualify in the paper. The marks
will not be included in determining the percentage of marks obtained for the award of a degree. However,
these marks will be shown in the detailed marks certificate of the students.
APTITUDE REASONING-II
Semester IV
Course code
Category PCC
Course title Aptitude Reasoning-II
3 0 0 3
Classwork 30 Marks
Exam 70 Marks
Total 100 Marks
Note: The examiner will set nine questions in total. Question one will be compulsory. Question one
will have seven parts of 2 marks each from all units, and the remaining eight questions of 14 marks
each to be set by taking two questions from each unit. The students have to attempt five questions
in total, the first being compulsory and selecting one from each unit.
COURSE OBJECTIVES:
This course is designed to suit the need of the outgoing students and to acquaint them with frequently
asked patterns in quantitative aptitude and logical reasoning during various examinations and campus
interviews.
COURSE OUTCOMES:
On successful completion of the course the students will be able to:
CO1. Understand the basic concepts of quantitative ability
CO2. Understand the basic concepts of logical reasoning Skills
CO3. Acquire satisfactory competency in use of reasoning
CO4. Solve campus placements aptitude papers covering Quantitative Ability, Logical Reasoning
Ability
CO5. Compete in various competitive exams like CAT, CMAT, GATE, GRE, GATE, UPSC, GPSC etc.
UNIT – I
Quantitative Ability I . Average, Problems on Ages, Surds & Indices, Percentages, Problems on
Numbers,
UNIT – II
Quantitative Ability II. Logarithm, Permutation and Combinations, Probability, Time & Work, Ratio
and Proportion, Mixtures and Allegation, Volume, Problem on boat and stream
UNIT – III
Data Interpretation. Data Interpretation, Pie Chart, Venn Diagrams
UNIT – IV
Logical Reasoning (Deductive Reasoning) Coding – Decoding, Calendars, Venn Diagrams, Seating
Arrangement, Syllogism, Mathematical Operations

1. A Modern Approach To Verbal & Non Verbal Reasoning By R S Agarwal
2. Analytical and Logical reasoning By Sijwali B S
3. Quantitative aptitude for Competitive examination By R S Agarwal
4. Analytical and Logical reasoning for CAT and other management entrance test By Sijwali B S
5. Quantitative Aptitude by Competitive Examinations by Abhijit Guha
COMPUTER ARCHITECTURE AND ORGANIZATION
Semester IV
Course code
Category PCC
Course title Computer Architecture and Organization
3 0 0 3
Classwork 30 Marks
Exam 70 Marks
Total 100 Marks
Note: The examiner will set nine questions in total. Question one will be compulsory. Question
one will have seven parts of 2 marks each from all units, and the remaining eight questions of
14 marks each to be set by taking two questions from each unit. The students have to attempt
five questions in total, the first being compulsory and selecting one from each unit.
COURSE OBJECTIVES:
The objectives of the course are:
1. Discuss the basic concepts and structure of computers.
2. Understand concepts of register transfer logic and arithmetic operations.
3. Explain different types of addressing modes and memory organization.
4. Learn the different types of serial communication techniques.
5. Summarize the Instruction execution stages.
COURSE OUTCOMES:
At the end of this course, students will be able to:
CO1. Understand the theory and architecture of central processing unit.
CO2. Analyze some of the design issues in terms of speed, technology, cost, performance.
CO3. Design a simple CPU with applying the theory concepts.
CO4. Use appropriate tools to design verify and test the CPU architecture.
CO5. Learn the concepts of parallel processing, pipelining and interprocessor communication.
CO6. Understand the architecture and functionality of central processing unit.
CO7. Exemplify in a better way the I/O and memory organization.
CO8. Define different number systems, binary addition and subtraction, 2’s complement
representation and operations with this representation.
UNIT-I
BOOLEAN ALGEBRA AND LOGIC GATES
Boolean algebra and Logic gates, Combinational logic blocks(Adders, Multiplexers, Encoders, de-
coder), Sequential logic blocks(Latches, Flip-Flops, Registers, Counters) Store program control
concept, Flynn’s classification of computers (SISD, MISD, MIMD); Multilevel viewpoint of a
machine: digital logic, micro architecture, ISA, operating systems, high level language; structured
organization; CPU, caches, main memory, secondary memory units & I/O; Performance metrics; MIPS,
MFLOPS.
UNIT -II
INSTRUCTION SET ARCHITECTURE
Instruction Set Architecture Instruction set based classification of processors (RISC, CISC, and their
comparison); addressing modes: register, immediate, direct, indirect, indexed; Operations in the
instruction set; Arithmetic and Logical, Data Transfer, Control Flow; Instruction set formats (fixed,
variable, hybrid); Language of the machine: 8086; simulation using MSAM.
UNIT -III
MEMORY HIERARCHY
Basic non pipelined CPU Architecture and Memory Hierarchy & I/O Techniques CPU Architecture
types (accumulator, register, stack, memory/ register) detailed data path of a typical register based CPU,
Fetch-Decode-Execute cycle (typically 3 to 5 stage); microinstruction sequencing, implementation of
control unit, Enhancing performance with pipelining. The need for a memory hierarchy (Locality of
reference principle, Memory hierarchy in practice: Cache, main memory and secondary memory,
Memory parameters: access/ cycle time, cost per bit); Main memory (Semiconductor RAM & ROM
organization, memory expansion, Static & dynamic memory types); Cache memory (Associative &
direct mapped cache organizations.
UNIT- IV
PARALLELISM AND INTERRUPTS
Introduction to Parallelism and Computer Organization [80x86] Goals of parallelism (Exploitation of
concurrency, throughput enhancement); Amdahl’s law; Instruction level parallelism (pipelining, super
scaling –basic features); Processor level parallelism (Multiprocessor systems overview). Instruction
codes, computer register, computer instructions, timing and control, instruction cycle, type of
instructions, memory reference, register reference. I/O reference, Basics of Logic Design, accumulator
logic, Control memory, address sequencing, micro-instruction formats, micro-program sequencer,
Stack Organization, Instruction Formats, Types of interrupts; Memory Hierarchy.
1. Computer Organization and Design, 2nd Ed., by David A. Patterson and John L. Hennessy,
Morgan 1997, Kauffmann.
2. Computer Architecture and Organization, 3rd Edi, by John P. Hayes, 1998, TMH.
3. Operating Systems Internals and Design Principles by William Stallings,4th edition, 2001,
Prentice-Hall Upper Saddle River, New Jersey
4. Computer Organization, 5th Edi, by Carl Hamacher, Zvonko Vranesic,2002, Safwat Zaky.
5. Structured Computer Organisation by A.S. Tanenbaum, 4th edition, Prentice-Hall of India,
1999, Eastern Economic Edition.
6. Computer Organisation & Architecture: Designing for performance by W. Stallings, 4th
edition, 1996, Prentice-Hall International edition.
7. Computer System Architecture by M. Mano, 2001, Prentice-Hall. 6.Computer Architecture-
Nicholas Carter, 2002, T.M.H.
ANALYSIS AND DESIGN OF ALGORITHMS
Semester IV
Course code
Category PCC
Course title Analysis and Design of Algorithms
3 0 0 3
Classwork 30 Marks
Exam 70 Marks
Total 100 Marks
COURSE OBJECTIVES:
1. The students should be able to analyze various algorithms mainly for time and space
complexity.
2. They should be able to develop algorithm for solving various computational problems by
applying various algorithm design strategies.
3. They should be able to understand the effect of choice of data structures on the complexity of
algorithm.
COURSE OUTCOMES:
At the end of the course, students will be able to:
CO1: Apply the best data structure for designing an algorithm to solve a given problem.
CO2: Evaluate different algorithms with respect to time and space complexity.
CO3: Create algorithms to solve various computational problems.
CO4: Understand different complexity classes.
CO5: Understand the sorting techniques
CO6: Explain the hardness of real world problems with respect to algorithmic efficiency and learning
to cope with it.
UNIT-I
BASIC CONCEPTS OF ALGORITHMS:
Basic Concepts of Algorithms: Notion of Algorithm, Fundamentals of Algorithmic Solving, Important
problem types, Fundamentals of the Analysis Framework, Asymptotic Notations and Basic Efficiency
Classes, Mathematical analysis of non-recursive algorithms. Mathematical analysis of recursive
algorithm: recurrence relations, solution of recurrence relations using substitution method
UNIT-II
SORTING ALGORITHMS:
Brute Force, Divide and Conquer Strategy: Selection sort, Bubble sort, Sequential searching (Linear
Search), Brute force string matching, General method, Merge sort, Quick Sort, Binary Search,
Strassen’s matrix multiplication
UNIT-III
GREEDY AND DYNAMIC PROGRAMMING:
Greedy Approach and Dynamic Programming: Fractional Knapsack problem, Minimum cost spanning
tree: Prim’s and Kruskal’s algorithm, Single source shortest path problem, Principle of optimality,
Multi-stage graph problem, all pair shortest path problem, 0/1 Knapsack problem, Traveling
salesperson problem
UNIT-IV
BACKTRACKING & BRANCH AND BOUND:
Backtracking and Branch and Bound: General method backtracking, N-Queen problem, 0/1 Knapsack
problem, General method of branch & bound, 0/1 Knapsack problem, Traveling sales person problem
Lower Bound Theory and Complexity Classes, Lower bounds, Decision trees, P, NP and NP Complete
problems
TEXT BOOKS AND REFERRENCE BOOKS:

1. Algorithm Design, Jon Kelinberg and Eva Tardos, 1st Edition, Pearson Education 2014.
2. Design & Analysis of Algorithms, Gajendra Sharma, Khanna Book Publishing 2018.
3. Fundamentals of algorithms, Horowitz E, Sahini S, Rajasekaran S., University Press 2008.
4. Introduction to algorithms, Cormen, Leiserson, Rivest, Stein, 3rd Edition, PHI. 2012
5. An introduction to analysis of algorithms, R. Sedgewick, 1st edition, Pearson Education 1996.
6. Data Structures and Program Design in C By Robert L. Kruse, C.L. Tondo, Bruce Leung, Pearson
Education. 2007.
AI DATA ANALYTICS USING R
Semester IV
Course code
Category PCC
Course title AI Data Analytics using R
3 0 0 3
Classwork 30 Marks
Exam 70 Marks
Total 100 Marks
COURSE OBJECTIVES:
1. In this course students will learn the basic concepts of data analysis
2. Perform data analytics, data visualisation and statistical model for data analytics.
COURSE OUTCOMES:
After completing this course, you will be able to:
CO1: Explain critical R programming concepts
CO2: Demonstrate how to install and configure RStudio
CO3: Explain the use of data structure and loop functions
CO4: Analyse data and generate reports based on the data
CO5: Apply various concepts to write programs in R
CO6: Understand different visualization techniques and applications using R
CO7: Analyze the statistical data using R
UNIT-I
INTRODUCTION TO DATA ANALYSIS:
Overview of Data Analytics, Need of Data Analytics, Nature of Data, Classification of Data: Structured,
Semi-Structured, Unstructured, Characteristics of Data, Applications of Data Analytics.
UNIT-II
R PROGRAMMING BASICS:
Overview of R programming, Environment setup with R Studio, R Commands, Variables and Data
Types, Control Structures, Array, Matrix, Vectors, Factors, Functions, R packages.
UNIT-III
DATA VISUALIZATION USING R:
Reading and getting data into R (External Data): Using CSV files, XML files, Web Data, JSON files,
Databases, Excel files. Working with R Charts and Graphs: Histograms, Boxplots, Bar Charts, Line
Graphs, Scatterplots, Pie Charts
UNIT-IV
STATISTICS WITH R:
Random Forest, Decision Tree, Normal and Binomial distributions, Time Series Analysis, Linear and
Multiple Regression, Logistic Regression,
Prescriptive Analytics: Creating data for analytics through designed experiments, Creating data for
analytics through active learning, Creating data for analytics through reinforcement learning

1. An Introduction to R, Notes on R: A Programming Environment for Data Analysis and Graphics.
W. N. Venables, D.M. Smith and the R Development Core Team. Version 3.0.1 (2013-05-16).
URL: https://cran.r-project.org/doc/manuals/r-release/R-intro.pdf
2. Jared P Lander, R for everyone: advanced analytics and graphics, Pearson Education, 2013.
3. Dunlop, Dorothy D., and Ajit C. Tamhane. Statistics and data analysis: from elementary to
intermediate. Prentice Hall, 2000.
4. G Casella and R.L. Berger, Statistical Inference, Thomson Learning 2002.
5. P. Dalgaard. Introductory Statistics with R, 2nd Edition. (Springer 2008)
6. Michael Berthold, David J. Hand, Intelligent Data Analysis, Springer
7. Hastie, Trevor, et al.The elements of statistical learning.Vol. 2. No. 1. New York: springer, 2009.
8. Montgomery, Douglas C., and George C. Runger.Appliedstatistics and probability for engineers.
John Wiley &Sons, 2010
9. Joseph F Hair, William C Black etal , “Multivariate Data Analysis” , Pearson Education, 7th
edition, 2013.
10. Mark Gardener, “Beginning R - The Statistical Programming Language”, John Wiley & Sons,
Inc., 2012.
11. W. N. Venables, D. M. Smith and the R Core Team, “An Introduction to R”, 2013.
CRYPTOGRAPHY AND SECURITY
Semester IV
Course code
Category PCC
Course title CRYPTOGRAPHY AND SECURITY
3 0 0 3
Classwork 30 Marks
Exam 70 Marks
Total 100 Marks
COURSE OBJECTIVES:
1. To understand basics of Cryptography and Network Security.
2. To be able to secure a message over insecure channel by various means.
3. To learn about how to maintain the Confidentiality, Integrity and Availability of a data.
4. To understand various protocols for network security to protect against the threats in the networks.
COURSE OUTCOMES:
After the completion of the course the students will be able
CO1. Discover all the Information Security Goals, Services & Mechanism for Network Security &
necessity of Mathematics in designing crypto algorithms.
CO2. Develop and design various kinds of Symmetric Key crypto algorithms and to cryptanalyze
them.
CO3. Construct and design various kinds of Asymmetric key crypto algorithms and Mathematics
required for designing.
CO4. Analyze the integrity of information transmitted & to generate digital signatures.
CO5. Predict and apply the knowledge and skills obtained to design & understand latest
cryptographic protocols used for securing information in networks or in storage.
UNIT-I
INTRODUCTION TO INFORMATION SECURITY & CRYPTOGRAPHY:
What is Information Security, Need for security, Principles of Security, Threats, Types of Attacks,
Services & Mechanisms, Mathematics of Cryptography: Integer Arithmetic, Modular Arithmetic,
Matrices, Linear Congruence
UNIT-II
SYMMETRIC KEY CIPHERS:
raditional Symmetric –Key Cipher design and analysis-Different Substitution ciphers & Transposition
ciphers, Basic Principles of designing Stream cipher & Block cipher.
Mathematics of Symmetric-Key Cryptography-Algebraic Structures, GF (2n) Fields.
Modern Symmetric key Ciphers- Block Ciphers Design & Analysis - Data encryption Standard(DES),
Advanced Encryption Standard (AES)
Stream Ciphers Design & Analysis-LFSR based, RC4, A5/1.
UNIT-III
ASYMMETRIC KEY CIPHERS, HASH FUNCTIONS AND DIGITAL SIGNATURES:
Mathematics of Asymmetric-Key Cryptography, Asymmetric key Ciphers, Hash Functions and MAC,
Introduction to Digital Signatures.
UNIT-IV
NETWORK SECURITY:
Network Security: Security at application layer – PGP & S/MIME, Key distribution Centre, Diffie-
Hellman Key Exchange.

1. Cryptography and Network Security 7th Edition, William Stallings
2. Cryptography and Network Security, 4rd edition, Forouzan & Mukopadhyay, TMH.
3. Information Security & Cryptography-Cryptography Made Simple, Nigel P Smart, Springer Verlag,
2016.
4. Cryptography & Network Security, 2nd Edition, Atul Kahate. McGrawHill
SOFT COMPUTING
Semester IV
Course code
Course title Soft Computing
3 0 0 3
Classwork 30 Marks
Exam 70 Marks
Total 100 Marks
COURSE OBJECTIVE:
1. To introduce soft computing concepts and techniques and foster their abilities in designing
appropriate technique for a given scenario.
2. To implement soft computing based solutions for real-world problems.
3. To give students knowledge of non-traditional technologies and fundamentals of artificial neural
networks, fuzzy sets, fuzzy logic, genetic algorithms.
4. To provide students; hand-on experience on MATLAB to implement various strategies.
COURSE OUTCOMES:
CO1: Identify and describe soft computing techniques and their roles in building
intelligent Machines.
CO2: Apply fuzzy logic and reasoning to handle uncertainty and solve various
engineering problems.
CO3: Apply genetic algorithms to combinatorial optimization problems.
CO4: Evaluate and compare solutions by various soft computing approaches for a given
problem.
UNIT - I
INTRODUCTION TO SOFT COMPUTING: Evolution of Computing: Soft Computing Constituents,
From Conventional AI to Computational Intelligence: Machine Learning Basics
UNIT - II
FUZZY LOGIC: Fuzzy Sets, Operations on Fuzzy Sets, Fuzzy Relations, Membership Functions:
Fuzzy Rules and Fuzzy Reasoning, Fuzzy Inference Systems, Fuzzy Expert Systems, Fuzzy Decision
Making.
UNIT - III
NEURAL NETWORKS: Machine Learning Using Neural Network, Adaptive Networks, Feed
forward Networks, Supervised Learning Neural Networks, Radial Basis Function Networks:
Reinforcement Learning, Unsupervised Learning Neural Networks, Adaptive Resonance
architectures, Advances in Neural networks
UNIT - IV
GENETIC ALGORITHMS: Introduction to Genetic Algorithms (GA), Applications of GA in
Machine Learning : Machine Learning Approach to Knowledge Acquisition.
1. George J. Klir and Bo Yuan, “Fuzzy Sets and Fuzzy Logic: Theory and Applications”, PHI
2. Satish Kumar, “Neural Networks: A classroom approach” Tata McGraw Hill.
3. Haykin S., “Neural Networks-A Comprehensive Foundations”, PHI
4. Anderson J.A., “An Introduction to Neural Networks”, PHI
5. M.Ganesh, “Introduction to Fuzzy sets and Fuzzy Logic” PHI.
6. N P Padhy and S P Simon, “Soft Computing with MATLAB Programming”, Oxford
University Press
CRYPTOGRAPHY AND SECURITY LAB
Semester IV
Course code
Course title Cryptography and Security Lab
0 0 2 1
Classwork 50 Marks
Exam 50 Marks
Total 100 Marks
COURSE OBJECTIVES:
1. To provide deeper understanding into cryptography, its application to network
security, threats/vulnerabilities to networks and countermeasures.
2. To explain various approaches to Encryption techniques, strengths of Traffic
Confidentiality, Message Authentication Codes.
3. To familiarize symmetric and asymmetric cryptography
COURSE OUTCOMES:
CO1: Identify basic security attacks and services
CO2: Use symmetric and asymmetric key algorithms for cryptography
CO3: Make use of Authentication functions
CO4: Implement different encryption and decryption algorithms
CO5: Implement key expansion algorithms
EXPERIMENTS
1. Program to find GCD of any two numbers a and b mod n by Generalized Euclidean Algorithm
2. Program to find Multiplicative Inverse of b in Zp, p prime by Generalized Euclidean Algorithm
3. Program to encrypt and decrypt by Ceaser Cipher
4. Program to Encrypt and Decrypt by Affine Cipher
5. Program to encrypt plaintext by Playfair Cipher
6. Program to generate addition and multiplication table for GF(22) Field
7. Program for key expansion algorithm of DES
8. Program to implement 4*4 S-box and perform two functionalities:
a.) Check given table of S-box and inverse S-box are invertible to each other.
b.) Ask the user to enter input to be given in S-box and return its output.
9. Program to implement encryption and decryption of RSA algorithm
ANALYSIS AND DESIGN OF ALGORITHMS LAB
Semester IV
Course code
Course title Analysis and Design of Algorithms Lab
0 0 2 1
Classwork 50 Marks
Exam 50 Marks
Total 100 Marks
COURSE OBJECTIVES:
The course should enable the students to:
1. Learn how to analyze a problem and design the solution for the problem.
2. Design and implement efficient algorithms for a specified application.
3. Strengthen the ability to identify and apply the suitable algorithm for the given real world
problem.
COURSE OUTCOMES:
CO1: Design algorithms using divide and conquer, greedy and dynamic programming.
CO2: Execute sorting algorithms such as sorting, graph related and combinatorial algorithm in a
high level language.
CO3: Analyze the performance of merge sort and quick sort algorithms using divide and conquer
technique.
CO4: Apply the dynamic programming technique to solve real world problems such as knapsack
and TSP.
EXPERIMENTS
. 1. Write a program to implement different sorting techniques.
• Bubble Sort
• Insertion Sort
• Selection Sort
• Quick Sort
• Merge Sort
2. Write a program to find minimum cost spanning tress.
3. Write a program to implement travelling sales person problem.
4. Write a program to find Longest Path in a Directed Acyclic Graph.
5. Write a program for Shortest path with exactly k edges in a directed and weighted graph.
6. Write a program find maximum number of edge disjoint paths between two vertices
7. Implement 0/1 Knapsack problem using Dynamic Programming.
8. Perform various tree traversal algorithms for a given tree.
9. Implement N-Queens Problem

AI DATA ANALYTICS USING R LAB
Semester IV
Course code
Course title AI Data Analytics using R Lab
0 0 2 1
Classwork 50 Marks
Exam 50 Marks
Total 100 Marks
COURSE OBJECTIVES:
The course should enable the students to:
1. Implement functions, analyze different datasets using R
2. Perform statistical analysis of data using R
3. Learn different visualization techniques
COURSE OUTCOMES:
CO1. Apply mathematical functions and build applications using R
CO2. Analyze different datasets using R
CO3. Visualize different parameters and interpret data
CO4. Finding relationships between variables involved using different regression models
CO5. Visualizing data using different plotting techniques
EXPERIMENTS
. 1. 1 R AS CALCULATOR APPLICATION
a) Using with and without R objects on console
b) Using mathematical functions on console
c) Write an R script, to create R objects for calculator application and save in a specified location in disk.
2 DESCRIPTIVE STATISTICS IN R
a) Write an R script to find basic descriptive statistics using summary, str, quartile function on mtcars&
cars datasets.
b) Write an R script to find subset of dataset by using subset (), aggregate () functions on iris dataset.
3 READING AND WRITING DIFFERENT TYPES OF DATASETS
a) Reading different types of data sets (.txt, .csv) from Web and disk and writing in file in specific disk
location.
b) Reading Excel data sheet in R.
c) Reading XML dataset in R.
4. VISUALIZATIONS
a) Find the data distributions using box and scatter plot.
b) Find the outliers using plot.
c) Plot the histogram, bar chart and pie chart on sample data.
5. REGRESSION MODEL
Import a data from web storage. Name the dataset and now do Logistic Regression to find out relation
between variables that are affecting the admission of a student in a institute based on his or her GRE score,
GPA obtained and rank of the student. Also check the model is fit or not. Require (foreign), require (MASS).
6. REGRESSION MODEL FOR PREDICTION
Apply regression Model techniques to predict the data on above dataset.
INDIAN CONSTITUTION
Semester IV
Course code
Category Audit Course
Course title Indian Constitution
2 0 0 0
Classwork 30 Marks
Exam 70 Marks
Total 100 Marks
COURSE OBJECTIVES:
1. Understand the premises informing the twin themes of liberty and freedom from a civil rights
perspective.
2. To address the growth of Indian opinion regarding modern Indian intellectuals’ constitutional
role and entitlement to civil and economic rights as well as the emergence of nationhood in
the early years of Indian nationalism.
3. To address the role of socialism in India after the commencement of the Bolshevik Revolution
in 1917 and its impact on the initial drafting of the Indian Constitution.
COURSE OUTCOMES:
At the end of the course, the student should be able to:
CO1: Discuss the growth of the demand for civil rights in India for the bulk of Indians before
the arrival of Gandhi in Indian politics.
CO2: Discuss the intellectual origins of the framework of argument that informed the
conceptualization of social reforms leading to a revolution in India.
CO3: Discuss the circumstances surrounding the foundation of the Congress Socialist Party
[CSP] under the leadership of Jawaharlal Nehru and the eventual failure of the proposal
of direct elections through adult suffrage in the Indian Constitution.
CO4: Discuss the passage of the Hindu Code Bill of 1956.
.
UNIT-I
PHILOSOPHY OF INDIAN CONSTITUTION: Salient features of Indian Constitution, Preamble, and
Nature of Indian Constitution, Procedure for amendment of the Constitution.
UNIT-II
FEDERAL STRUCTURE: Federal structure and distribution of legislative and financial powers
between the Union and the States
UNIT-III
ORGANS OF GOVERNANCE: President – Qualification and Powers of the President, Governor-
Qualification and Powers of Governor,
PARLIAMENT: Composition, Qualifications and Disqualifications, Judiciary: Appointment,
Tenure and Removal of Judges.
UNIT-IV
FUNDAMENTAL RIGHTS: Origin and development of Fundamental rights, Need for fundamental
rights. Introduction to Rights to equality, right to freedom, right against exploitation, Right to
freedom of religion, Cultural and Education rights and Fundamental duties.
1. The Constitution of India, 1950 (Bare Act), Government Publication.
2. Dr. S.N. Busi, Dr. B.R. Ambedkar framing of Indian Constitution, latest Edition
3. M.P. Jain, Indian Constitution Law, Lexis Nexis, latest edition
4. D.D. Basu, Introduction to Constitution of India, Lexis Nexis, latest edition.
5
th
SEMESTER
(Cyber Security)
Semester V
S. Category Course Course Title Hours per Credit Marks Marks for Total
No Code week s for End Term
L T P
al n
1 PCC Database Management
3 0 0 3 30 70 100
Systems
2 PCC Theory of Computation 3 0 0 3 30 70 100
3 PCC Programming in JAVA 3 0 0 3 30 70 100
4 PCC Block Chain Technology 3 0 0 3 30 70 100
5 OEC Open Elective I 3 0 0 3 30 70 100
6 PEC Professional Elective I 3 0 0 3 30 70 100
7 BSC Communication and
3 0 0 3 30 70 100
Interpersonal Skills
8 LC Database Management
0 0 2 1 50 50 100
Systems Lab (P)
9 LC Programming in JAVA
0 0 2 1 50 50 100
Lab (P)
10 LC Block Chain Technology
0 0 2 1 50 50 100
Lab (P)
Practical Training-I 0 0 2 1 50 50 100
Total 21 0 8 25 1100
NOTE:
1. Choose any one from Professional Elective Course – I
2. Choose any one from Open Elective Course – I*
Professional Elective Course – I

1. Introduction to Physical and Systems Security
2. Software Security and Trusted Systems
3. Biometrics and its Applications
4. Cyber Security Threats
* Open Elective Course – I : To be chosen from the bucket of Open Elective Course-I
DATABASE MANAGEMENT SYSTEMS
Semester V
Course code
Category Professional Core Courses
Course title Database Management Systems
3 0 0 3
Classwork 30 Marks
Exam 70 Marks
Total 100 Marks
COURSE OBJECTIVES:
1. To understand the different issues involved in the design and implementation of a database
system.
2. To study the physical and logical database designs, database modeling, relational, hierarchical,
and network models
3. To understand and use data manipulation language to query, update, and manage a database
4. To develop an understanding of essential DBMS concepts such as: database security, integrity,
concurrency, distributed database, and intelligent database, Client/Server (Database Server), Data
Warehousing.
5. To design and build a simple database system and demonstrate competence with the fundamental
tasks involved with modeling, designing, and implementing a DBMS.
COURSE OUTCOMES:
CO1. For a given query, write relational algebra expressions for that query and optimize the
developed expressions
CO2. For a given requirement specification, design the databases using E R method and
normalization.
CO3. For a given specification, construct the SQL queries for Open source and Commercial
DBMS - MYSQL, ORACLE, and DB2.
CO4. For a given query, optimize its execution using Query optimization algorithms
CO5. For a given transaction-processing system, determine the transaction atomicity, consistency,
isolation, and durability.
CO6. Implement the isolation property, including locking, and time stamping based on
concurrency control and Serializability of scheduling.
UNIT - I
Database system architecture: Data Abstraction, Data Independence, Data Definition Language (DDL), Data
Manipulation Language (DML).
Data models: Entity-relationship model, network model, relational and object-oriented data models,
integrity constraints, data manipulation operations.
UNIT - II
Relational query languages: Relational algebra, Tuple and domain relational calculus, SQL3, DDL and
DML constructs, Open source and Commercial DBMS - MYSQL, ORACLE, DB2, SQL server. Relational
database design: Domain and data dependency, Armstrong's axioms, Normal forms, Dependency
preservation, Lossless design.
Query processing and optimization: Evaluation of relational algebra expressions, Query equivalence, Join
strategies, Query optimization algorithms.
UNIT - III
Transaction processing: Concurrency control, ACID property, Serializability of scheduling, Locking and
timestamp-based schedulers, Multi-version and optimistic Concurrency Control schemes, Database
recovery.
Storage strategies: Indices, B-trees, hashing,
UNIT - IV
Database Security: Authentication, Authorization and access control, DAC, MAC and RBAC models,
Intrusion detection, SQL injection.
Advanced topics: Object-oriented and object-relational databases, Logical databases, Web databases,
Distributed databases, Data warehousing and data mining.
1. Database System Concepts, 6th Edition by Abraham Silberschatz, Henry F. Korth, S. Sudarshan,
McGraw-Hill
2. Principles of Database and Knowledge–Base Systems, Vol 1 by J. D. Ullman, Computer Science
Press.
3. Fundamentals of Database Systems, 5th Edition by R. Elmasri and S. Navathe, Pearson
Education
4. Foundations of Databases, Reprint by Serge Abiteboul, Richard Hull, Victor Vianu, Addison-
Wesley
THEORY OF COMPUTATION
Semester V
Course code
Course title Theory of Computation
3 0 0 3
Classwork 30 Marks
Exam 70 Marks
Total 100 Marks
COURSE OBJECTIVES:
1. To understand basic concepts of formal languages and automata theory.
2. To study the types of Automata i.e., NFA, DFA, NFA with ϵ-transition and their interconversion
methods and importance.
3. To Study formal languages of different kinds, such as regular and context-free languages. Understand
the concept of grammar and its types. Removal of ambiguity and reduced form and Normal forms of
grammar.
4. To develop the concepts and design of higher-level automata to accept the language not accepted by
finite automata such as PDA &Turing machine.
5. To study the various properties of Turing machines and their design.
COURSE OUTCOMES:
CO1: Define terminology related to the theory of computation.
CO2: Explain the basic concepts and applications of Theory of Computation.
CO3: Apply the principles of Theory of Computation to solve computational problems.
CO4: Compare and contrast the hierarchy of grammars.
CO5: Design various types of automata for given problems.
CO6: To solve various problems of applying normal form techniques, push-down automata, and
Turing Machines.
UNIT - I
Finite Automata: Introduction: Set, Power Set, Super Set, Alphabet, languages and grammars,
productions and derivation, Deterministic finite automata (DFA), Non-Deterministic finite automata
(NDFA), Equivalence of DFA and NDFA, Conversion of NFA to DFA, minimization of finite automata,
Finite automata with ϵ- moves, Acceptability of a string by a finite Automata.
Introduction to Machines: Properties and limitations of Finite Automata, Mealy and Moore Machines,
Equivalence of Mealy and Moore machines.
UNIT - II
Regular Expression: State and prove Arden’s Method, Regular Expressions, Recursive definition of the
regular expression, Regular expression conversion to Finite Automata, and vice versa.
Properties of regular languages: Regular language, pumping lemma for regular sets/languages, Application of
regular languages.
UNIT - III
Grammars: Chomsky hierarchy of languages, Relation between different types of grammars, Context-
free grammar, Derivation tree / Parse tree, Ambiguity in regular grammar and their removal,
Reduced Forms: Removal of useless symbols, null and unit productions, Normal Form: Chomsky Normal
form (CNF) and Greibach Normal Form (GNF),
Push Down Automata: Introduction to PDA, Deterministic and Non-Deterministic PDA, Design of
PDA: Transition table, Transition diagram and acceptability of strings by designed PDA, Pushdown
automata (PDA) and equivalence with CFG.
UNIT - IV
Turing machines: The basic model for Turing machines I, Deterministic and Non- Deterministic Turing
machines and their equivalence, Design of Turing Machines: Transition table, Transition diagram and
acceptability of strings by a designed Turing machine. Variants of Turing machines, Halting problem of
Turing machine, PCP Problem of Turing Machine, Linear Bounded Automata, TMs as enumerators.
Undecidability: Church-Turing thesis, universal Turing machine, the universal and diagonalization
languages, reduction between languages and Rice s theorem, undecidable problems about languages.
1. Introduction to Automata Theory, Languages, and Computation, 3nd Edition, John E. Hopcroft, Rajeev
Motwani, Jeffrey D. Ullman, Pearson Education.
2. Introduction to the Theory of Computation, Michael Sipser, 3rd edition, Cengage Learning.
3. K. L. P Mishra, N. Chandrashekaran (2003), Theory of Computer Science-Automata Languages and
Computation, 2nd edition, Prentice Hall of India, India.
4. Raymond Greenlaw, H. James Hoover, Fundamentals of the Theory of Computation, Principles and
Practice, Morgan Kaufmann, 1998.
5. John C. Martin: Introduction to Languages and Automata Theory, 3rd edition, Tata McGraw- Hill,
2007
PROGRAMMING IN JAVA
Semester V
Course code
Course title Programming in JAVA
3 0 0 3
Classwork 30 Marks
Exam 70 Marks
Total 100 Marks
COURSE OBJECTIVES:
1. Explore advanced topic of Java programming for solving problems
2. Be able to put into use the advanced features of the Java language to build and compile robust
enterprise- grade applications
3. Provide a sound foundation to the students on the concepts, precepts and practices, in a field that is
of immense concern to the industry and business
4. Design and develop GUI applications using Swings
5. Enhance knowledge to manipulate and store data
6. To provide foundations on Java Beans, Struts and JSON
7. To analyze the object-oriented paradigm using java programming language
COURSE OUTCOMES:
CO1: Identify classes, objects, members of a class and relationships among them for a specific
problem.
CO2: Understand and demonstrate the concepts of garbage collection, polymorphism, inheritance etc.
CO3: Do numeric (algebraic) and string-based computation.
CO4: Understand and implement modularity as well as basic error-handling techniques.
CO5: Develop, design and implement small multithreaded programs using Java language.
CO6: Apply appropriate problem-solving strategies for the implementation of small/medium scale Java
applications
UNIT-I
INTRODUCTION TO JAVA: Evolution of Java, Object Oriented Programming Structure, Overview and
characteristics of Java, Java program Compilation and Execution Process, Organization of the Java
Virtual Machine, Client side Programming, Platform Independency & Portability, Security, Relation
b/w JVM, JRE and JDK, Introduction to JAR format, Naming Conventions, Data types & Type casting,
operators, Security Promises of the JVM, Security Architecture and Security Policy, security aspects,
sandbox model.
UNIT-II
OOPS IMPLEMENTATION: Classes, Objects, attributes, methods, data encapsulation, reference
variables, Constructors, Anonymous block, Method Overloading, Static Data members, Block &
methods; Memory Structure: Stack, Heap, Class & Method area
Class loading & Execution ﬂow: Static vs Dynamic Class loading, implicit vs explicit class loading,
class loading operations;
Argument Passing Mechanism: Passing primitive arguments, passing objects, Wrapper Classes; This
keyword: Referencing instance members, Intra class constructor chaining, Method chaining; Inheritance
& code reusability: Extending classes for code reusability, Usage of super keyword, Method
Overriding, Object class
INHERITANCE & RUNTIME POLYMORPHISM: Static & Dynamic binding, Inheritance and Is-A
relation, Runtime Polymorphism and Generalization, Abstract classes & methods, Final Keyword;
Interfaces and Role based Inheritance: Feature & Role based Inheritance, Static & Dynamic classing
Environment, classes & interfaces, interface applications in real scenarios; Has-A relation:
Aggregation & Composition, Nested classes, Inner classes, Anonymous Inner classes, String Buffer
Class, tokenizer, applets, Life cycle of applet and Security concern
UNIT-III
THREADS: Creating Threads, Thread Priority, Blocked States, Extending Thread Class, Runnable
Interface, Starting Threads, Thread Synchronization, Synchronize Threads, Sync Code Block, Overriding
Synced Methods, Thread Communication, wait, notify and notify all.
SWING & AWT:
Swing class hierarchy, containers, user interface components, graphics context, AWT Components,
Component Class, Container Class, Layout Manager Interface Default Layouts, Insets and Dimensions,
Border Layout, Flow Layout, Grid Layout, Card Layout Grid Bag Layout AWT Events, Event Models,
Listeners, Class Listener, Adapters, Action Event Methods Focus Event Key Event, Mouse Events,
Window Event
PACKAGE & SCOPES: Need of Packages, associating classes to Packages, Class path environment
variable, Import Keyword and Feature of static import, Public, protected, private & default scope, Private
Inheritance;
EXCEPTION HANDLING: exception and error, Exception Handling & Robustness, Common Exceptions
and Errors, Try and catch block, Exception handlers, throw keyword, Checked and Unchecked
Exceptions, Role of finally, User defined Exceptions.
UNIT-IV
COLLECTION FRAMEWORK: Role and Importance of Collection Framework, List & Set based
collection, Iterator & List Iterator, Maps, Searching elements in List, Hash and Tree based collections,
Role of equals and hashCode() methods, Comparable and Comparator Interfaces, Thread Safety and
Vector, Difference b/w Enumeration and Iterator, Type safety and Generics, Common algorithms and
Collections class, Using Properties class for managing properties files;
Database Connectivity Using JDBC: Overview of native and ODBC Drives, Introduction to JDBC, Type
of JDBC drivers, Usage of drivers, defining properties-based Connection Factory; Basic database
operations: Insert, Delete, Update, and Select;
Prepared Statement: Statement, Prepared Statement, Setting Query parameters, Executing Queries;
1. E. Balaguruswamy, “Programming with Java”, TMH
2. Horstmann, “Computing Concepts with Java 2 Essentials”, John Wiley.
3. Decker &Hirshfield, “Programming.Java”, Vikas Publication.
4. Patrick Naughton and HerbertzSchidt, “Java-2 the complete Reference”, TMH
5. Sierra & bates, “Head First Java”, O’Reilly.
BLOCK CHAIN TECHNOLOGY
Semester V
Course code
Course title Block Chain Technology
3 0 0 3
Classwork 30 Marks
Exam 70 Marks
Total 100 Marks
COURSE OBJECTIVES:
1. To enable the student to understand and appreciate, the importance of fundamentals of blockchain
technology and application of cryptography in blockchain
2. To gain the awareness about the concepts of various implementations of blockchain technology
such as bitcoin, Ethereum, and Hyper ledger
COURSE OUTCOMES:
CO1. Student will be able to understand the fundamentals of blockchain technology.
CO2. Apply knowledge of implementations of Bitcoin to develop solutions in the appropriate
domains.
CO3. Apply knowledge of implementations of Ethereum to develop solutions in the appropriate
domains.
CO4. Apply knowledge of implementations of Hyperledger to develop solutions in theappropriate
domains.
CO5. Explore the blockchain technology to apply in real world problems of cryptography domains
UNIT-I
INTRODUCTION TO BLOCKCHAIN TECHNOLOGY: Distributed systems – The history of
blockchain – Introduction to blockchain – CAP theorem and blockchain – Benefits and limitations of
blockchain – Decentralization using blockchain - Methods of decentralization – Routes to
decentralization
UNIT-II
CRYPTOGRAPHY IN BLOCKCHAIN: Introduction – cryptographic primitives – Assymetric
cryptography – public and private keys -line interface – Bitcoin improvement proposals (BIPs) –
Consensus Algorithms.
UNIT-III
BITCOIN: Introduction – Transactions – Structure - Transactions types – The structure of a block– The
genesis block – The bitcoin network– Wallets and its types– Bitcoin payments– Bitcoin investment and
buying and selling bitcoins – Bitcoin installation – Bitcoin programming and the command-line
interface – Bitcoin improvement proposals (BIPs).
UNIT-IV
ETHEREUM: Ethereum block chain- Elements of the Ethereum block chain– Precompiled contracts –
Accounts and its types – Block header- Ether – Messages – Mining - Clients and wallets – Trading and
investment – The yellow paper - The Ethereum network - Applications developed on Ethereum -
Scalability and security issues
1. Bashir, Mastering Blockchain: Distributed ledger technology, decentralization, and smart
contracts explained, 2nd Edition, 2nd Revised edition edition. Birmingham: Packt Publishing,
2018.
2. M. Antonopoulos, Mastering bitcoin, First edition. Sebastopol CA: O‘Reilly,2015.
3. Z. Zheng, S. Xie, H. Dai, X. Chen, andH. Wang, ―An Overviewof Blockchain Technology:
Architecture, Consensus, and Future Trends,‖ in 2017 IEEE International Congress on Big
Data (BigData Congress), 2017, pp.557–564.
COMMUNICATION AND INTERPERSONAL SKILLS
Semester V
Course code
Course title Communication and Inter Personal Skills
3 0 0 3
Classwork 30 Marks
Exam 70 Marks
Total 100 Marks
COURSE OBJECTIVES:
To enhance holistic development of students and improve their employability skills. Provide a 360degree
exposure to learning elements of Business English readiness program, behavioral traits, achieve softer
communication levels. To up skill and upgrade students’ across varied industry needs to enhance
employability skills. By the end of this semester, the student will have entered the employability
enhancement and skill building activity exercise.
COURSE OUTCOMES:
CO1. At the end of the session a student would have learned what is VMOSA (Vision, Mission, Values
and Ethics) and Communication Process. This would help students understand and interpret the
deeper meaning of life.
CO2. At the end of the session a student would have learned Communication Styles and flexing and 4
social styles of communication which will lead to effective and meaningful communication
process along with Listening Styles & Listening Skills.
CO3. At the end of the session a student would have learned the Art of giving feedback, assess and
evaluate real life situations better.
CO4. At the end of the session a student would have learned business writing skills and non-verbal
communication process to make an impression in written communication process in office or
otherwise coupled with positive body language and non-verbal communication.
CO5. A student will learn to probe skills that will help in improving peer to peer and business
communication
UNIT- I
IMPRESS TO IMPACT: What is Personality?, Creating a positive impression – The 3 V‘s of Impression,
Individual Differences and Personalities, Personality Development and Transformation ,Building Self
Confidence.
UNIT-II
BEHAVIORAL AND INTERPERSONAL SKILLS: Avoiding Arguments, The Art of Assertiveness,
Constructive Criticism, The Personal Effectiveness Grid, Assessing our Strengths & Limitations and
Creating an Action Plan for Learning with the 4M Model, Verbal Abilities
UNIT-III
POSITIVE THINKING & ATTITUDE BUILDING: Goal Setting and SMART Goals – Milestone
Mapping | Enhancing L S R W G and P (Listening Speaking Reading Writing Grammar and
Pronunciation), VMOSA (Vision, Mission, Values and Ethics), Business Communication - Verbal
Communication Skills, Barriers in communication, Basics of effective communication – PRIDE Model
UNIT-IV
COMMUNICATIONS: Different styles of communication & style flexing (Based on the 4 social styles-
Analytical, Driving, Expressive, Amiable), Importance of Listening & practice of Active Listening,
Email Etiquette, Business Writing Skill, Telephone Etiquette Skills (Telephone Handling Skills), Non-
Verbal Communication-Kinesics, Proxemics, Paralanguage, MTI Reduction Program.
1. Power of Positive Action (English, Paperback, Napoleon Hill)
2. Streets of Attitude (English, Paperback, Cary Fagan, Elizabeth Wilson)
3. The 6 Pillars of self-esteem and awareness – Nathaniel Brandon
4. Goal Setting (English, Paperback, Wilson Dobson
PROGRAMMING IN JAVA LAB
Semester V
Course code
Category Lab Courses
Course title Programming in JAVA Lab
0 0 2 1
Classwork 50 Marks
Exam 50 Marks
Total 100 Marks
COURSE OUTCOMES:
At the end of this course, students will demonstrate the ability to:
CO1. Implement Java programs using object-oriented concepts for problem solving.
CO2. Detect syntax and logical errors in java programs.
CO3. Apply exception handling for making robust JAVA code.
CO4. Design java applications using File I/O and GUI.
CO5. Create lab record of the solutions of assignments that includes problem definitions, solutions
and conclusions.
CO6. Demonstrate ethical practices, self-learning and team spirit.
EXPERIMENTS
1. Create a java program to implement stack and queue concept.
2. Write a java package to show dynamic polymorphism and interfaces.
3. Write a java program to show multithreaded producer and consumer application.
4. Create a customized exception and also make use of all the5 exception keywords.
5. Convert the content of a given file into the upper-case content of the same file.
6. Develop an analog clock using applet.
7. Develop a scientific calculator using swings.
8. Create an editor like MS-word using swings.
9. Create a servlet that uses Cookies to store the number of times a user has visited your servlet.
10. Create a simple java bean having bound and constrained properties.
DATABASE MANAGEMENT SYSTEM LAB
Semester V
Course code
Course title Database Management System Lab
0 0 2 1
Classwork 50 Marks
Exam 50 Marks
Total 100 Marks
COURSE OUTCOMES:
CO1. Understand basic concepts of database system and data models for relevant problems.
CO2. Understand the basic elements of a relational database management system.
CO3. Design entity relationship model and convert entity relationship diagrams into RDBMS and
formulate SQL queries on the data.
CO4. Apply normalization for the development of application software.
EXPERIMENTS
1. Creation of a database and writing SQL queries to retrieve information from the database.
2. Performing Insertion, Deletion, Modifying, Altering, Updating and Viewing records based
on conditions.
3. Creation of Views, synonyms, Sequences, indexes, and save points.
4. Creating an employee database to set various constraints.
5. Creating relationships between the databases. iv. Study of PL/SQL block.
6. Write a PL/SQL block to satisfy some conditions by accepting input from the user.
7. Write a PL/SQL block that handles all types of exceptions.
8. Creation of Procedures
9. Creation of database triggers and functions
10. Mini project (Application Development using Oracle/ MySQL)
11. Inventory Control System
12. Material Requirement Processing.
13. Hospital Management System.
14. Railway Reservation System.
15. Personal Information System.
16. Web-Based User Identification System.
17. Time Table Management System.
18. Hotel Management
BLOCK CHAIN TECHNOLOGIES LAB
Semester V
Course code
Course title Block Chain Technologies Lab
0 0 2 1
Classwork 50 Marks
Exam 50 Marks
Total 100 Marks
COURSE OBJECTIVES
This course will enable the students:
1. Understanding Block chain Fundamentals and creating basic blocks.
2. Able to Develop Block chain Applications in a structured manner
3. Ability to create own crypto currency and get familiarity with future currencies.
4. Able to Evaluate and Analyze Block chain Systems
COURSE OUTCOMES
CO1. Knowledge of Blockchain Concepts and creating basic blocks.
CO2. Proficiency in Blockchain Development.
CO3. Ability to Design and Implement Blockchain Applications.
CO4. Evaluation and Analysis of Blockchain Systems.
CO5. Knowledge of crypto currency and creating a basic form of it.
EXPERIMENTS
1. Creating Merkle tree
2. Creation of Block
3. Block chain Implementation Programming code
4. Creating ERC20 token
5. Java code to implement blockchain in Merkle Trees
6. Java Code to implement Mining using block chain
7. Java Code to implement peer-to-peer using block chain
8. Creating a Crypto-currency Wallet
PRACTICAL TRAINING - I
Semester V
Course code
Course title Practical Training - I
0 0 2 1
Classwork 50 Marks
Exam 50 Marks
Total 100 Marks
The evaluation of Practical Training - I will be based on the seminar, viva voice, and report submitted by the
students. According to performance, the students are awarded grades A, B, C, F. A student who is awarded an
‘F’ grade is required to repeat Practical Training.
A Excellent
B Good
C Satisfactory
F Not Satisfactory
Professional
INTRODUCTION TO PHYSICAL AND SYSTEMS SECURITY
Semester V
Course code
Category Professional Elective Course
Course title Introduction to Physical and Systems Security
3 0 0 3
Classwork 30 Marks
Exam 70 Marks
Total 100 Marks
be set by taking two questions from each unit. The students have to attempt five questions in total,
the first being compulsory and selecting one from each unit.
COURSE OBJECTIVES:
To provide students with:
1. Physical, technical and procedural controls, including good environment design and premises
security
2. Understanding issues involved in security
3. Reducing risks when moving data
4. Securely disposing of data
5. Maintaining security in delivery area
COURSE OUTCOMES:
CO1: understand and implement physical and software security
CO2: Apply software security issues
CO3: Maintain security measures and apply in real world problems
CO4: Reduce security risks in different areas
CO5: Perform virtualization security in different fields
UNIT-I
OVERVIEW OF PHYSICAL SECURITY: Physical Security Threats, Physical Security Prevention and
Mitigation Measures, Recovery from Physical Security breaches, Integration of Physical and Logical
Security
UNIT-II
INTRODUCTION TO SOFTWARE SECURITY: Software Security Issues, Handling Program Input,
Writing Safe Program Code, Interacting with Operating Systems and Other Programs, Handling
Program Output
UNIT –III
INTRODUCTION TO OPERATING SYSTEM SECURITY: System Security Planning, Operating
System Hardening, Application security, Security Maintenance, Linux/Unix Security, Windows
Security, Virtualization Security
UNIT-IV
INTRODUCTION TO HUMAN RESOURCES SECURITY: security Awareness, Training and
Education, employment Practices and Policies, Email and Internet use Policies, Computer Security
Incident Response Teams

1. Industrial Network Security: Securing Critical Infrastructure Networks for Smart Grid,
SCADA, and Other Industrial Control Systems 2nd Edition
2. Applied Cyber Security and the Smart Grid: Implementing Security Controls into the
Modern Power Infrastructure 1st Edition
SOFTWARE SECURITY AND TRUSTED SYSTEMS
Semester V
Course code
Course title Software Security and Trusted Systems
3 0 0 3
Classwork 30 Marks
Exam 70 Marks
Total 100 Marks
one will have seven parts of 2 marks each from all units, and the remaining eight questions of 14
marks each to be set by taking two questions from each unit. The students have to attempt five
questions in total, the first being compulsory and selecting one from each unit.
COURSE OBJECTIVES:
1. Understand the issues of software security and apply in real world problems
2. Learn different models for computer security
3. Study of different internet authentication
COURSE OUTCOMES:
CO1. Understand the issues of software security
CO2. Emphasize different types of software security
CO3. Choose different models and applications for system security
CO4. Understand different wireless security in areas
CO5. Learn applications of internet authentication
UNIT-I
INTRODUCTION TO SOFTWARE SECURITY AND ITS ISSUES: Writing safe program code,
interacting with Operating System and Other programs, Handling Program Output, Introduction to
Operating System Security, Computing and Multilevel Security
UNIT-II
OPERATING SYSTEM SECURITY: System Security Planning, Operating System Hardening,
Application Security, Security Maintenance, Linux/Unix Security, Windows Security, Virtualization
Security
UNIT-III
BELL-LAPULA MODEL FOR COMPUTER SECURITY: Formal Models for Computer Security,
Concept of Trusted Systems, Application of Multilevel Security, Trusted computing and Trusted
Platform Module, Common criteria for Security Evaluation, assurance and Evaluation
UNIT-IV
WIRELESS AND MOBILE SECURITY: Wireless Security, Mobile Device Security, IEEE 802.11
Wireless LAN Overview and its Security, SSL and transport Layer Security, Internet Authentication
Applications: Kerberos. X.509.
1. The Web Application Hacker's Handbook: Finding and Exploiting Security Flaws by Dafydd
Stuttard and Marcus Pinto
2. Applied Cryptography: Protocols, Algorithms, and Source Code in C by Bruce Schneier
BIOMETRICS AND ITS APPLICATIONS
Semester V
Course code
Course title Biometrics and its Applications
3 0 0 3
Classwork 30 Marks
Exam 70 Marks
Total 100 Marks
COURSE OBJECTIVES:
1. To understand the basics of biometrics and its functionalities
2. To learn the role of biometric in the organization
3. To learn to develop applications with biometric security
COURSE OUTCOMES:
CO1. Summarize biometrics overview and applications
CO2. Choose suitable security techniques for biometric
CO3. Identify the multidisciplinary technologies for biometric applications
CO4. Designing models for Physiological and Behavioral Systems
CO5. Applying components and algorithms for pattern recognition
CO6. Apply different applications of Biometrics
UNIT-I
INTRODUCTION TO BIOMETICS:
What is Biometrics, Biometric Systems, Evolution of Biometrics, Basic Components of Biometric
System, General Working of Biometric Systems, Biometric Terminologies, Application Areas of
Biometrics, Types of Biometric Modalities
UNIT-II
PHYSIOLOGICAL AND BEHAVIORAL MODALITIES:
Fingerprint Recognition System, Facial Recognition System, Iris Recognition System, Retinal
Scanning System, Hand Geometry Recognition System, DNA Recognition System, Gait
Recognition. Signature Recognition System, Keystroke Recognition System, Voice Recognition
System, Difference between voice and speech recognition
UNIT-III
MULTIMODAL BIOMETRIC SYSTEMS:
Need of Multimodal Biometric, working of multimodal biometric systems, design issues with
multimodal biometric, criteria for effective biometric system, comparison of biometric modalities,
performance measurements
UNIT-IV
BIOMETRICS AND APPLICATIONS:
Pattern Recognition in Biometrics, Components in Pattern Recognition, Algorithms in Pattern
Recognition, Signal Processing in Biometrics, Digital Signal Processing Systems, DSP in
Biometrics, Image Processing in Biometrics, Biometric System Security and Risks involved.

1. Handbook of Biometrics, by Anil K. Jain, Patrick Flynn, Arun A. Ross.
2. J.L. Wayman, A. Jain, D. Maltoni, and D. Maio, Biometric Systems Technology, Design and
Performance Evaluation, Springer , ISBN: 9781852335960
3. Guide to Biometrics, R. M. Bolle, S. Pankanti, N.K. Ratha, A. W. Senior, J. H. Connell,
Springer 2009 ISBN 978-0387400891,
4. A.A. Ross, K. Nandakumar, and A.K. Jain, Handbook of Multibiometrics, Springer , ISBN:
9780387222967.
CYBER SECURITY THREATS
Semester V
Course code
Category Professional Elective Courses
Course title Cyber Security Threats
3 0 0 3
Classwork 30 Marks
Exam 70 Marks
Total 100 Marks
COURSE OBJECTIVES:
1. The learner will gain knowledge about securing both clean and corrupted systems,
protect personal data, and secure computer networks.
2. The learner will understand key terms and concepts in cyber law, intellectual property
and cybercrimes, trademarks and domain theft.
3. The learner will be able to examine secure software development practices.
4. The learner will understand principles of web security.
5. The learner will be able to incorporate approaches for risk management and best practices.
6. The learner will gain an understanding of cryptography, how it has evolved, and some
key encryption techniques used today.
COURSE OUTCOMES:
CO1: Analyze and resolve security issues in networks and computer systems to secure
an IT infrastructure.
CO2: Design, develop, test and evaluate secure software.
CO3: Develop policies and procedures to manage enterprise security risks.
CO4: Evaluate and communicate the human role in security systems with an emphasis
on ethics, social engineering vulnerabilities and training.
CO5: Interpret and forensically investigate security incidents.
UNIT - I
INTRODUCTION: Security threats - Sources of security threats- Motives - Target Assets and
vulnerabilities – Consequences of threats- E-mail threats - Web-threats - Intruders and Hackers, Insider
threats, Cyber crimes. Network Threats: Active/ Passive – Interference – Interception – Impersonation
– Worms –Virus – Spam’s – Ad ware - Spy ware – Trojans and covert channels – Backdoors – Bots –
IP, Spoofing - ARP spoofing - Session Hijacking - Sabotage-Internal treats Environmental threats -
Threats to Server security.
UNIT - II
SECURITY THREAT MANAGEMENT: Risk Assessment - Forensic Analysis - Security threat
correlation –Threat awareness - Vulnerability sources and assessment- Vulnerability assessment tools
–Threat identification - Threat Analysis - Threat Modelling - Model for Information Security Planning.
UNIT - III
SECURITY ELEMENTS: Authorization and Authentication - types, policies and techniques – Security
certification - Security monitoring and Auditing - Security Requirements Specifications – Security
Policies and Procedures, Firewalls, IDS, Log Files, Honey Pots
UNIT - IV
ACCESS CONTROL: Trusted Computing and multilevel security - Security models, Trusted Systems,
Software security issues, Physical and infrastructure security, Human factors – Security awareness,
training, Email and Internet use policies.

1. Swiderski, Frank and Syndex, “Threat Modeling”, Microsoft Press, 2004.
2. William Stallings and Lawrie Brown, “Computer Security: Principles and Practice”, Prentice
Hall, 2008.
3. Joseph M Kizza, “Computer Network Security”, Springer Verlag, 2005
4. Thomas Calabres and Tom Calabrese, “Information Security Intelligence: Cryptographic
Principles & Application”, Thomson Delmar Learning, 2004.
th
6
(Cyber Security)
Semester VI
L T P al
1 PCC Computer 3 0 0 3 30 70 100
Networks
2 PCC Cyber for Data
Science and its 3 0 0 3 30 70 100
applications
3 PCC Intrusion Detection 3 0 0 3 30 70 100
Systems
4 PEC Professional
3 0 0 3 30 70 100
Elective –II
5 OEC Open-Elective-II 3 0 0 3 30 70 100
PEC Professional 3 0 0 3 30 70 100
Elective -III
7 LC Computer 0 0 2 1 50 50 100
Networks Lab (P)
8 LC Cyber for Data 0 0 2 1 50 50 100
Science and its
applications Lab (P)
9 PROJ Project-I 0 0 4 2 50 50 100
Total 18 0 8 22 900
NOTE:
1. At the end of the 6th semester, each student has to undergo Practical Training of 4/6 weeks in an
Industry/ Institute/ Professional Organization/ Research Laboratory/ training center etc. and
submit the typed report along with a certificate from the organization & its evaluation shall be
carried out in the 7th Semester.
2. Choose any one from Professional Elective Course – II & III
3. Choose any one from Open Elective Course – II*
Professional Elective Course – II
1. Cyber Crimes and Laws
2. Database and Cloud Security
3. Malware Analysis and Reverse Engineering
4. Steganography & Digital Watermarking
Professional Elective Course – III

1. Software Testing and Project Management
2. Data Mining and Warehousing
3. Social network Analysis
4. Cryptocurrency with Ethereum
*Open Elective Course – II : To be chosen from the bucket of Open Elective Course-II
NOTE: At the end of 6th semester each student has to undergo Practical Training of 4/6 weeks in an
Industry/Institute/ Professional Organization/Research Laboratory/ training centre etc. and submit typed
report along with a certificate from the organization & its evaluation shall be carried out in the 7th
Semester.
COMPUTER NETWORKS
Semester VI
Course code
Category PCC
COMPUTER NETWORKS
Course title
Credits 3 0 0 3
Class work 30 Marks
Exam 70 Marks
Total 100 Marks
in total, the first being compulsory and selecting one from each unit
COURSE OBJECTIVES:
1. To develop an understanding of modern network architectures from a design and
Performance perspective.
2. To introduce the student to the major concepts involved in wide-area networks
(WANs), local area networks (LANs), and Wireless LANs (WLANs).
3. To provide an opportunity to do Network programming.
4. To provide WLAN measurement ideas.
COURSE OUTCOMES:
CO1: Explain the functions of the different layers of the OSI Protocol.
CO2: Draw the functional block diagram of wide-area networks (WANs), local area
networks (LANs), and Wireless LANs (WLANs) and describe the function of each.
CO3: Identify and connect various connecting components of a computer network.
CO4: Configure DNS DDNS, TELNET, EMAIL, File Transfer Protocol (FTP), WWW,
HTTP, SNMP, Bluetooth, and Firewalls using open-source available software and tools.
CO5: outline various models, topologies and devices of Computer Networks.
UNIT - I
INTRODUCTION:
Data communication, Components, Data Representation, Simplex, Half Duplex, and Full Duplex
Transmission, Modulation, Multiplexing, Computer networks, distributed processing, Internet,
Topologies, Packet and circuit switching, connectionless and connection- oriented services.
Network Models: OSI model and TCP/IP Model Physical Layer – LAN: Ethernet.
UNIT - II
DATA LINK LAYER AND MEDIUM ACCESS SUB LAYER: MAC Addressing, Framing, Stop and
Wait, Go back – N ARQ, Selective Repeat ARQ, Sliding Window Protocol.
MEDIUM ACCESS CONTROL: Random access, Controlled Access, and channelization protocols.
NETWORK LAYER: Logical addressing, classful and classless addressing, subnetting, Ipv4,
ICMPv4, ARP, RARP and BOOTP, Ipv6, Ipv6 addressing.
UNIT - III
NETWORK DEVICES: Repeater, hub, switch, router, and gateway.
ROUTING ALGORITHMS: Introduction to routing, Shortest Path Algorithm, Flooding,
Hierarchical Routing, Link State, and Distance Vector Routing
TRANSPORT LAYER: Process to Process Communication, User Datagram Protocol
(UDP), Transmission Control Protocol (TCP), TCP connection management.
UNIT - IV
APPLICATION LAYER: Congestion Control, Quality of Service, QoS Improving techniques,
Domain Name Space (DNS), EMAIL, File Transfer Protocol (FTP), HTTP, SNMP
NETWORK SECURITY: Firewalls, security goals, types of attack, symmetric and
asymmetric key ciphers.
1. Data Communication and Networking, 4th Edition, Behrouz A. Forouzan, McGraw-Hill.
2. Data and Computer Communication, 8th Edition, William Stallings, Pearson Prentice Hall
India.
3. Computer Networks, latest Edition, Andrew S. Tanenbaum, Pearson New International
Edition.
4. Internetworking with TCP/IP, Volume 1, latest Edition Douglas Comer, Prentice Hall of
India.
5. TCP/IP Illustrated, Volume 1, W. Richard Stevens, Addison-Wesley, United States of
America.
CYBER FOR DATA SCIENCE AND ITS APPLICATIONS
Semester VI
Course code
Category PCC
Cyber for Data Science and its Applications
Course title
Credits 3 0 0 3
Class work 30 Marks
Exam 70 Marks
Total 100 Marks
COURSE OBJECTIVES:
This courses makes the students understand the basics of data science and its applications for cyber
security.
COURSE OUTCOMES:
On successful completion of this course students will be able to:
CO 1 Understand and implement the basics of programming in Python.
CO 2 Understand and implement the Collections in Python.
CO 3 Apply Object Oriented Programming concepts on real world examples.
CO 4 Apply the Numpy package for numerical calculations in Python.
CO 5 Apply Pandas package for loading and preprocessing data in Python.
.
UNIT –I
BASICS OF PYTHON AND THEIR DATA TYPES:
Variables and Identifiers , Operators, Expressions and Data Types, What Is a Control Structure,
Boolean Expressions (Conditions), Relational Operators, Membership Operators, Selection Control,
Multi-Way Selection, Iterative Control, While Statement , Infinite loops, Definite vs. Indefinite
Loops, Boolean Flags and Indefinite Loops, List Structures, Common List Operations, Tuples ,
Nested Lists, For Loops , While Loops and Lists (Sequences), Assigning and Copying Lists ,
Dictionary Type in Python, Set Data Type , Program Routines , Defining Functions, More on
Functions , Calling Value-Returning Functions, Calling Non-Value- Returning Functions, Parameter
Passing, Arguments in Python Default Arguments in Python, Variable Scope, Recursive Function
UNIT-II
NUMPY:
Creation on Array, Array generation from Uniform distribution, Random array generation, reshaping,
maximum and minimum, reshaping, Arithmetic operations, Mathematical functions, Bracket
Indexing and Selection, Broadcasting, Indexing a 2D array (matrices);
UNIT-III
PANDAS:
Creating a Series - from lists, arrays and dictionaries, Storing data in series from intrinsic sources,
Creating DataFrames, Imputation, Grouping and aggregation, Merging, Joining, Concatenation,
Find Null Values or Check for Null Values, Reading data from csv, txt, excel
UNIT-IV
VISUALIZATION USING MATPLOTLIB: Installing and setting up visualization libraries, Canvas
and Axes, Subplots, Common plots – scatter, histogram, boxplot, Logarithmic scale, Placement of
ticks and custom tick labels, Pandas Viz, Style Sheets, Plot type, Area, Barplots, Histograms, Line
Plots, Scatter Plots, BoxPlots, Hexagonal Bin Plot, Kernel Density Estimation plot (KDE),
Distribution Plots, Categorical Data Plots,
Combining Categorical Plots, Matrix Plots, Regression Plots, Grids.

1. Charles Dierbach., Introduction to Python using Computer Science, Wiley Publications,
Second Edition, 2015
2. Mark Lutz , Learning Python, O’Reilly publications , Fifth Edition, 2015
3. Introduction to linear algebra - by Gilbert Strang
4. Applied statistics and probability for engineers – by Douglas Montgomery
5. Mastering python for data science, Samir Madhavan
INTRUSION DETECTION SYSTEM
Semester VI
Course code
Category PCC
Course title Intrusion Detection Systems
Credits 3 0 0 3
Class work 30 Marks
Exam 70 Marks
Total 100 Marks
Duration of
03 Hours
Exam
each to be set by taking two questions from each unit. The students have to attempt five
COURSE OBJECTIVES:
1. Compare alternative tools and approaches for Intrusion Detection through quantitative
analysis to determine the best tool or approach to reduce risk from intrusion.
2. Identify and describe the parts of all intrusion detection systems and characterize newand
emerging IDS technologies according to the basic capabilities all intrusion detection systems
share.
COURSE OUTCOMES:
CO1. Possess a fundamental knowledge of Cyber Security.
CO2. Understand the vulnerability in network and address common vulnerabilities.
CO3. Know basic and fundamental risk management principles as it relates to IDPS
CO4. Analyse the network behaviour and prevention techniques
CO5. Understand and analyse host based IDPS
CO6. Understand and analyse Multiple IDPS Technologies
CO7. Analyse various IDPS Products
UNIT-I
IDPS TECHNOLOGIES AND NETWORK-BASED IDPS:
Components & Architecture – Network architecture, Securities capabilities- information gathering,
logging, detection, prevention capabilities, Management- Implementation, operation & maintenance,
building & maintaining skills Networking Overview- Application Layer, Transport Layer, Network
Layer, Hardware Layer,Components and Architecture, Typical Components, Network Architectures
and Sensor Locations, Security Capabilities, Information Gathering Capabilities, Logging
Capabilities, Detection Capabilities, Prevention Capabilities, Management- Implementation,
Operation and Maintenance
UNIT-II
NETWORK BEHAVIOR ANALYSIS:
Components and Architecture, Typical Components, Network Architecture Sensor Locations,
Security Capabilities-Information Gathering Capabilities, Logging Capabilities, Detection
Capabilities, Prevention Capabilities, Management, Implementation, Operation and Maintenance
UNIT-III
HOST BASED IDPS:
Components and Architecture, Typical Components,Network Architectures, Agent Locations, Host
Architectures, Security Capabilities, Logging Capabilities, Detection Capabilities, Prevention
Capabilities, Other Capabilities.
UNIT-IV
IDPS TECHNOLOGIES:
The Need for Multiple IDPS Technologies, Integrating Different IDPS Technologies, Direct IDPS
Integration, Indirect IDPS, Integration OtherTechnologies with IDPS Capabilities, Network Forensic
Analysis Tool (NFAT) Software, Anti- Malware Technologies, Firewalls and Routers, Honeypots,
General Requirements, Security Capability Requirements, Performance Requirements, Life Cycle
Costs, Evaluating Products, IDPS Testing Challenges, Recommendations for IDPS Evaluations

1. Guide to Intrusion Detection and Prevention Systems- Karen Scarfone Peter Mell- Computer
Security Division Information Technology Laboratory National Institute of Standards and
Technology Gaithersburg, National Institute of Standards and Technology Special Publication
800-94
2. Tim Crothers, Implementing Intrusion Detection Systems: A Hands–On Guide forSecuring
the Network, John Wiley and Sons.
3. Christopher Kruegel, FedrickValeur, Intrusion Detection and Correlation: Challenges and
Solutions, Springer.
COMPUTER NETWORKS LAB
Semester VI
Course code
Course title COMPUTER NETWORKS LAB
0 0 2 1
Classwork 50 Marks
Exam 50 Marks
Total 100 Marks
COURSE OBJECTIVES:
Learn basic concepts of computer networking and acquire practical notions of protocols with the
emphasis on TCP/IP. A lab provides a practical approach to Ethernet/Internet networking: networks are
assembled, and experiments are made to understand the layered architecture and how do some important
protocols work.
COURSE OUTCOMES: ·
After completing the course, students will be able to:
CO1. Understand the structure and organization of computer networks; including the division into
network layers, role of each layer, and relationships between the layers. ·
CO2. Understand the basic concepts of application layer protocol design; including client/server
models, peer to peer models, and network naming.
CO3. In depth understanding of transport layer concepts for congestion control and flow control.
CO4. Learning protocol design; including connection oriented and connection-less models,
techniques to provide reliable data delivery and algorithms
CO5. Applying and configuring virtual LANS
EXPERIMENTS
1. To construct a simple network topology on Packet Tracer.
2. To verify and configure VLAN and VLAN trunk in packet tracer.
3. To construct RJ45 cable.
4. a) To configure simple static routing.
b) To implement Security on interconnecting devices.
5. To configure a Network Topology constitutes Routers and Switches using Packet Tracer.
6 Working with complex network topologies.
7. Mid Term Evaluation
8. To monitor network traffic using Wire Shark
9. To get the MAC or Physical Address of the system Using Address Resolution Protocol.
10. To Configure network using Routing Information Protocol (RIP)
11 To configure network state routing protocol (OSPF).
12 To configure Border Gateway Protocol.
13 To configure Application Layer protocols: DHCP and DNS.
CYBER FOR DATA SCIENCE AND ITS APPLICATIONS LAB
Semester VI
Course code
Course title Cyber for Data Science and its Applications LAB
0 0 2 1
Classwork 50 Marks
Exam 50 Marks
Total 100 Marks
COURSE OBJECTIVES:
1. Understand the process of Importing and Exporting the data.
2. Learn how to collect, store and manage data from multiple data sources.
3. Know the insights of data using statistical methods
4. Identify different techniques for data analysis and data visualization.
5. Discuss the applications of Data Science for real world problems.
COURSE OUTCOMES:
After completion of the course, students would be able to:
CO1. Examine the process for importing and exporting the data.
CO2. Apply appropriate data collection and pre-processing methods.
CO3. Identify different data analysis Techniques suitable for a given application
CO4. Demonstrate data visualization techniques for Data Analysis.
CO5. Applying the concepts of data science in cyber applications
EXPERIMENTS
1. Take Kaggle dataset CyberCrimeIndia and perform following operations:
2. Total number of features
3. Total number of missing values
4. Total number of unique values
5. Finding correlation matrix
6. Finding rate of total cyber crimes (2018)
7. Finding total number of categorical features
8. Performing Label Encoding on dataset
9. Splitting data into training and testing datasets and performing hot-encoding categorical features
10. Finding plot for one hot-encoder
11. Finding graph for mean estimated rate of cyber crimes 2018
12. Plot minimum estimated cyber crimes 2017.
13. Plot minimum percentage share of state/UT
14. Plot rate of total cyber crimes in 2017 and 2018
15. Plot mid-year projected population in 2016, 2017 and 2018
16. Plot rate of cyber crimes and mid-year projected population in 2018.
Professional
II
CYBER CRIMES AND LAWS
Semester VI
Course code
Category PEC
Course title Cyber Crimes and Laws
Credits 3 0 0 3
Class work 30 Marks
Exam 70 Marks
Total 100 Marks
COURSE OBJECTIVES:
This paper intends to create an understanding towards the cyber crimes and to familiarise the students
with the application of cyber laws in general.
COURSE OUTCOMES:
CO1. Make Learner Conversant With The Social And Intellectual Property Issues Emerging From
‘Cyberspace.
CO2. Explore The Legal And Policy Developments In Various Countries To Regulate Cyberspace;
CO3. Develop The Understanding Of Relationship Between Commerce And Cyberspace; And
CO4. Give Learners In Depth Knowledge Of Information Technology Act And Legal Frame Work
of Right To Privacy, Data Security And Data Protection.
CO5. Make Study On Various Case Studies On Real Time Crimes.
UNIT-I
CYBER CRIMES:
Introduction — Computer Crime and Cyber Crimes: Distinction between Cyber Crime and
Conventional Crimes; Cyber Forensic; Kinds of Cyber Crimes — Cyber Stalking, Cyber Terrorism,
Forgery and Fraud, Crimes Related to IPRs, Computer Vandalism: Privacy of Online Data; Cyber
Jurisdiction; Copyright Issues; Domain Name Dispute, etc.
UNIT-II
DEFINITION AND TERMINOLOGY (INFORMATION TECHNOLOGY ACT, 2000):
Concept of Internet, Internet Governance, E-contract, E-forms, Encryption, Data Security. Access,
Addressee, Adjudicating Officer, Affixing Digital Signatures, Appropriate Government, Certifying
Authority, Certification Practice Statement, Computer, Computer Network, Computer Resource,
Computer System, Cyber Appellate Tribunal, Data, Digital Signature, Electronic Form, Electronic
Record, Information, Intermediary, Key Pair, Originator, Public Key, Secure System, Verify,
Subscriber as defined in the Information Technology Act, 2000.
UNIT-III
ELECTRONIC RECORDS:
Authentication of Electronic Records; Legal Recognition of Electronic Records; Legal Recognition
of Digital Signatures; Use of Electronic Records and Digital Signatures in Government and its
Agencies; Retention of Electronic Records; Attribution, Acknowledgement and Dispatch of
Electronic Records; Secure Electronic Records and Digital Signatures.
UNIT- IV
REGULATORY FRAMEWORK:
Regulation of Certifying Authorities; Appointment and Functions of Controller; License to Issue
Digital Signatures Certificate; Renewal of License; Controller’s Powers; Procedure to be Followed
by Certifying Authority; Issue, Suspension and Revocation of Digital Signatures Certificate, Duties
of Subscribers; Penalties and Adjudication; Appellate Tribunal; Offences.
1. Marjie T. Britz Computer Forensic & Cyber Crime : An Introduction.
2. Karnika Seth Cyber Laws in the Information Technology Age
3. Aparna Vishwanathan Cyber Law Indian and International Perspectives
4. Prof.Vimlendu Tayal Cyber Law ,Cyber Crime, Cyber Internet and ECommerce.
5. Marjie T. Britz, “Computer Forensics and Cyber Crime”, Pearson, 2013.
6. Garima Tiwari, “Understanding Laws– Cyber Laws And Cyber Crimes”, Lexis Nexis, 2014.
7. Chuck Easttom, Jeff Taylor, “Computer Crime, Investigation, and the Law”, Course Technology,
2018.
8. Eoghan Casey, “Digital Evidence and Computer Crime: Forensic Science, Computers, and the
Internet”, Eoghan Casey, 2018
DATABASE AND CLOUD SECURITY
Semester VI
Course code
Category PEC
Course title Database and Cloud Security
Credits 3 0 0 3
Class work 30 Marks
Exam 70 Marks
Total 100 Marks
Duration of
03 Hours
Exam
questions in total, the first being compulsory and selecting one from each unit
COURSE OBJECTIVES:
This course helps the students to understand the concepts of database and cloud with different
methods of security.
COURSE OUTCOMES:
The course helps the students to
CO1. Explain the role of security in the design and implementation of databases
CO2. Use best practices for data input, output, and encryptions
CO3. Maintain database management systems, including conducting security audits and keeping
software updated
CO4. Understand the apply the concepts of SQL Injection attacks
CO5. Apply data protection in the cloud with different types of services
UNIT-I
Introduction to Database, Need of Database Security, Principles of Database Management Systems,
Elements of Relational DBMS, SQL, SQL commands: DDL, DML and DCL
UNIT-II
SQL Injection Attacks and their types, SQLi Countermeasures, Techniques of Injection, Database
Access Control: SQL-Based Access, Cascading Authorizations, Role Based Access Control,
Inference, Database Encryption
UNIT-III
Introduction to Cloud Computing and its elements, Cloud Computing Reference Architecture,
Cloud Computing Risks and countermeasures
UNIT-IV
Data Protection in the Cloud, Cloud Security as a Service, SaaS, PaaS, IaaS, Identity and Access
management, Data loss prevention, Email security, security information and event management

1. Michael Gertz and Sushil Jajodia, “Handbook of Database Security— Applications and
Trends”, Springer, 2008.
2. Bryan and Vincent, “Web Application Security, A Beginners Guide ”, McGraw-Hill, 2011
3. Bhavani Thuraisingham, “Database and Applications Security”, Integrating Information
Security and Data Management, Auerbach Publications, 2005.
4. Alfred Basta, Melissa Zgola, “Database Security”, Course Technology, 2012.
MALWARE ANALYSIS AND REVERSE ENGINEERING
Semester VI
Course code
Category PEC
Course title Malware Analysis & Reverse Engineering
Credits 3 0 0 3
Class work 30 Marks
Exam 70 Marks
Total 100 Marks
Course Title Malware Analysis & Reverse Engineering
COURSE OBJECTIVES:
1. Participants will be able to perceive malware analysis with open source.
2. Able to analyze and recognize malware with basic analysis techniques, dynamic analysis
techniques, and static analysis techniques
COURSE OUTCOMES:
CO1. To build an isolated and controlled laboratory environment to analyze code and behaviour of
malicious programs.
CO2. To list up basic analysis techniques
CO3. To reveal and do basic dynamic analysis of malicious JavaScript and other components of
web pages, which are often used by exploit kits for drive-by attacks.
CO4. To explain techniques of malicious code analysis, code debugging, malware debugging, and
kernel debugging.
CO5. To explain various features/packages of self-protected malware and other defence
mechanisms designed by malware makers to direct, confuse, and slow down analysts.
UNIT-I
INTRODUCTION TO MALWARE:
What is malware, malware infection channels, introduction to malware analysis, purpose of analysis,
step-by-step process of malware analysis, types of analysis, malware analysis stages/flow, virtual
machine, virtual networks, tools of malware analysis and components of malware analysis, malware
acquisition, malware defense
UNIT-II
STATIC AND DYNAMIC ANALYSIS:
Introduction to Static Analysis: File Types, Strings, File Hash, File Resource, DLL Imports, Sandbox,
PE Headers, Timestamp and Packer Identification, Introduction to Dynamic Analysis: Network
Monitoring, File System Monitoring, Windows Registry Monitory, Process Activity Monitoring,
Sandboxing, Dynamic Analysis Tools
UNIT-III
MALWARE FUNCTIONALITY:
Code Debugging, Breakpoints, exceptions, User/Kernel Mode, Malware Behavior, Covert Malware
Launching, Data Encoding, Malware-Focused Network Signatures
UNIT-IV
ANTI-REVERSE-ENGINEERING:
Introduction to Reverse Engineering, Anti Reverse Engineering, Anti-Disassembly, Anti-Debugging,
Anti-Virtual Machine Techniques, Packers and Unpacking
1. Michael Sikorski and Andrew Honig, “Practical Malware Analysis: The Hands-On Guide to
Dissecting Malicious Software”, No Starch Press,2012.
2. Practical Malware Analysis: The Hands-On Guide to Dissecting Malicious Software.
Author(s): Michael Sikorski, Andrew Honig (Text book) https://repo.zenk-security.com/Virus-
Infections-DetectionsPreventions/Practical_Malware_Analysis.pdf
3. Learning Malware Analysis: Explore the concepts, tools, and techniques to analyze and
investigate Windows malware. Author(s): Monnappa K A
4. Mastering Malware Analysis, Author(s): Alexey Kleymenov, Amr Thabet
5. https://zeltser.com/malware-analysis-cheat-sheet/
6. https://zeltser.com/analyzing-malicious-documents/
7. https://zeltser.com/remnux-malware-analysis-tips/
8. https://zeltser.com/malware-analysis-webcast/
STEGANOGRAPHY & DIGITAL WATERMARKING
Semester VI
Course code
Category PEC
Course title Steganography & Digital Watermarking
Credits 3 0 0 3
Class work 30 Marks
Exam 70 Marks
Total 100 Marks
COURSE OBJECTIVES:
1. To develop an understanding of digital watermarking and steganography basics, various
approaches, characteristics and application domains
2. To apply digital watermarking as an authentication tool for distribution of content over the
Internet and steganography techniques for covert communication
3. To understand the basics of the counter measures like steganalysis for assessing the data
hiding methods
4. To enable to evaluate and choose appropriate data hiding technique based on a multitude of
security factors
COURSE OUTCOMES:
After completion of this course, the student shall be able to:
CO1. Describe watermarking and steganography fundamental concepts and principles.
CO2. Identify and assess different types of data hiding techniques in various image formats like
GIF, BMP etc., and various data hiding methods like LSB, EzStego, OutGuess, and F5.
CO3. Describe the block codes and its usage for covert communication
CO4. Demonstrate the use of watermarking for copyright protection and steganography for
secret communication in various digital media
CO5. Design and implement efficient data hiding methods
CO6. Assess the strength of any data hiding algorithm against steganalysis techniques.
UNIT- I
INTRODUCTION:
Information Hiding, Steganography, and Watermarking. History of Watermarking. History of
Steganography, Importance of Digital Watermarking. Importance of Steganography.
UNIT- II
APPLICATIONS AND PROPERTIES OF WATERMARKING AND STEGANOGRAPHY:
Applications of Watermarking: Broadcast Monitoring, Owner Identification, Proof of Ownership,
Transaction Tracking, Content Authentication, Copy Control, Device Control, Legacy Enhancement,
Applications of Steganography: For Dissidents, for Criminals, Properties of Watermarking Systems:
Enbedding Effectiveness, Fidelity, Data Payload, Blind Detection, False Positive Rate, Robustness,
security, Cipher and Watermark Keys, Evaluating Watermarking Systems: Benchmarking, Scope of
Testing, Properties of Steganographic and Steganalysis Systems: Embedding Effectiveness, Fidelity,
Data Payload, Blind Extraction, False Alarm Rate, Robustness, security, Stego Keys
UNIT- III
MODELS OF WATERMARKING:
Notation, Communications, Components of Communications Systems, Classes of Transmission
Channels, Secure Transmission, Communication-Based Models of Watermarking, Basic Model,
Watermarking as Communications with Side Information at the Transmitter, Watermarking as
Multiplexed Communications, Geometric Models of Watermarking, Distributions and Regions in
Media Space, Marking Spaces, Modelling Watermark Detection by Correlation, Linear Correlation,
Normalized Correlation, Correlation Coefficient
UNIT IV
STEGANOGRAPHY AND STEGANALYSIS:
Steganographic Communication: The Channel, The Building
Blocks, Notation and Terminology, Information-Theoretic Foundations of Steganography, Cachin’s
Definition of Steganographic Security, Practical Steganographic Methods, Statistics Preserving
Steganography, Model-Based Steganography, Masking Embedding as Natural Processing,
Minimizing the Embedding Impact, Matrix Embedding, Nonshared Selection Rule, Steganalysis
Scenarios, Detection, Forensic Steganalysis, The Influence of the Cover Work on Steganalysis, Some
Significant Steganalysis Algorithms, LSB Embedding and the Histogram Attack, Sample Pairs
Analysis, Blind Steganalysis of JPEG Images Using Calibration, Blind Steganalysis in the Spatial
Domain.

1. I. J. Cox, M. L. Miller, J. A. Bloom, T. Kalker, and J. Fridrich, Digital Watermarking and
Steganography, 2nd Ed. Amsterdam: Morgan Kaufmann Publishers In, 2007. (ISBN No.: 978-
0-12-372585-1)
2. J. Fridrich, Steganography in Digital Media: Principles, Algorithms, and Applications.
Cambridge: Cambridge University Press, 2009. (ISBN No.: 978-0-52-119019-0)
3. R. C. Gonzalez, R. E. Woods, D. J. Czitrom, and S. Armitage, Digital Image Processing, 3rd Ed.
United States: Prentice Hall, 2007. (ISBN No.: 978-0-13-168728-8)
4. P. Wayner, Disappearing Cryptography: Information hiding: Steganography and Watermarking,
3rd ed. Amsterdam: Morgan Kaufmann Publishers In, 2008. (ISBN No.: 978-0-08-092270-6)
5. M. Arnold, M. Schmucker, and S. D. Wolthusen, Techniques and applications of digital
Watermarking and content protection, 2nd Ed. Boston, MA: Artech House Publishers, 2003.
(ISBN No.: 978-1-58-053664-6)
Professional
Elective
Course-III
DATA MINING AND WAREHOUSING
Semester VI
Course code
Category PEC
Course title Data Mining and Warehousing
3 0 0 3
Class work 30 Marks
Exam 70 Marks
Total 100 Marks
COURSE OBJECTIVES:
This course is designed to expand students' knowledge and skills gained in Data Mining and
Warehousing courses and look in depth at data warehousing and data mining methods. The course
examines the database architecture and technologies required for solving complex problems of data
and information management, information retrieval, and knowledge discovery facing modern
organizations. Case studies of organizations using these technologies to support business intelligence
gathering and decision making are examined. This course also provides hands-on experience with state-
of-the-art data warehousing and data mining methods and tools.
COURSE OUTCOMES:
After the completion of the course the students will be able
CO1. To understand Concept of Data Mining, Data warehousing and schemas for
multidimensional Databases.
CO2. To understand Basic Statistics in order to apply data mining techniques.
CO3. To analyse the data, identify the problems, and choose the relevant models and algorithms
to apply.
CO4. To combine and consolidate data from various databases scattered throughout a company
into a Datawarehouse.
CO5. To characterize the kinds of patterns that can be discovered by association rule mining,
classification and clustering.
UNIT-I
BASIC STATISTICS:
Statistical descriptions of data: mean, median, mode, Measuring dispersion of data: range, quartiles,
variance, standard deviation, chi-square test, Correlation coefficient and covariance, Regression
analysis.
UNIT-II
DATA PREPROCESSING:
Introduction to Data preprocessing, Need to preprocess the data, Data cleaning: missing values, Data
integration: Redundancy, Data reduction and its strategies, Data transformation and discretization,
Strategies of data transformation.
UNIT-III
INTRODUCTION TO DATA MINING AND ITS ALGORITHMS:
Introduction to Data Mining and algorithms, Processes, Market Basket Analysis, The Apriori
Algorithm, Decision Tree.
INTRODUCTION TO DATA WAREHOUSING AND DATA WRANGLING:
Data Warehouse, Difference between Operational Database systems and Data Warehouse, From Table
and Spreadsheets to Data Cubes, Schemas for Multidimensional Databases: Star, Snowflakes and Fact
Constellations, Data Wrangling, Combining and Merging DataSets, Reshaping and Pivoting, Data
Transformation, String Manipulation, Regular Expressions (Regex)
UNIT-IV
ETL:
ETL Phase 1 Data Wrangling before the Load, ETL Phase 2 Step-by-step guide to uploading data using
SSIS, Handling errors during ETL Phases 1,2, ETL Phase 3 Data Wrangling after the load, Handling
errors during ETL Phase 3, Different types of ETL tools.

1. Jiawei Han, Micheline Kamber and Jian Pei, “Data Mining Concepts and Techniques”, Third
Edition, Elsevier, 2011.
2. Alex Berson and Stephen J. Smith “Data Warehousing, Data Mining & OLAP”, Tata McGraw
– Hill Edition, Tenth Reprint 2007
3. K.P. Soman, Shyam Diwakar and V. Ajay “Insight into Data mining Theory and Practice”,
Easter Economy Edition, Prentice Hall of India, 2006
4. G. K. Gupta “Introduction to Data Mining with Case Studies”, Easter Economy Edition,
Prentice Hall of India, 2006.
5. Pang-Ning Tan, Michael Steinbach and Vipin Kumar “Introduction to Data Mining”, Pearson
Education, 2007.
SOFTWARE TESTING AND PROJECT MANAGEMENT
Semester VI
Course code
Category PEC
Course title SOFTWARE TESTING AND PROJECT MANAGEMENT
Credits 3 0 0 3
Class work 30 Marks
Exam 70 Marks
Total 100 Marks
Duration of
03 Hours
Exam
COURSE OBJECTIVES:
1. This course introduces the concepts and methods required for the construction of large software
intensive systems.
2. The course aims is to develop a broad understanding of the discipline of software engineering and
management of software systems.
3. This course provides an understanding of both theoretical and methodological issues involve in
modern software engineering project management and focuses strongly on Practical techniques.
COURSE OUTCOMES:
Upon the completion of the course students will be able to :
CO1. Apply the process to be followed in the software development life-cycle models.
CO2. Implement communication, modeling, construction & deployment practices in software
development.
CO3. Analyze & design the software models using unified modeling language (UML)
CO4. Explain the concepts of various software testing methods & be able to apply appropriate
testing approaches for development of software
CO5. Explain the quality management & different types of metrics used in software development.
CO6. Apply the concepts of project management & planning.
UNIT-I
SOFTWARE TESTING INTRODUCTION:
Introduction to Software Testing: Introduction, Evolution of Software Testing, Software Testing—
Myths and Facts, Goals of Software Testing, Psychology for Software Testing, Software Testing
Definitions, Model for Software Testing, Effective Software Testing vs. Exhaustive Software Testing,
Effective Testing is Hard, Software Testing as a Process, Software Testing Terminology, Software
Testing Life Cycle (STLC), Software Testing Methodology
UNIT-II
TESTING TECHNIQUES:
Dynamic Testing: Black-Box Testing Techniques, Boundary Value Analysis (BVA), Equivalence
Class Testing, State Table-Based Testing, Decision Table-Based Testing, Cause-Effect Graphing
Based Testing, Error Guessing, Dynamic Testing: White-Box Testing Techniques, Need of White-Box
Testing, Logic Coverage Criteria, Basis Path Testing, Graph Matrices, Loop Testing, Data Flow
Testing, Mutation Testing
Static Testing, Inspections, Structured Walkthroughs, Technical Reviews, Validation Activites, Unit
Validation Testing, Integration Testing, Function Testing System Testing, Acceptance Testing
UNIT-III
INTRODUCTION TO SOFTWARE PROJECT MANAGEMENT (SPM):
Definition of a Software Project (SP), SP Vs. other types of projects activities covered by SPM,
categorizing SPs, project as a system, management control, requirement specification, information and
control in organization.
Stepwise Project planning: Introduction, selecting a project, identifying project scope and objectives,
identifying project infrastructure, analyzing project characteristics, identifying project products and
activities, estimate efforts each activity, identifying activity risk, allocate resources, review/ publicize
plan.
UNIT-IV
PROJECT EVALUATION & ESTIMATION:
Cost benefit analysis, cash flow forecasting, cost benefit evaluation techniques, risk evaluation.
Selection of an appropriate project report; Choosing technologies, choice of process model, structured
methods, rapid application development, water fall, V-process, spiral models. Prototyping, delivery.
Albrecht function point analysis. Activity planning & Risk Management: Objectives of activity
planning, project schedule, projects and activities, sequencing and scheduling activities, network
planning model, representation of lagged activities, adding the time dimension, backward and forward
pass,
identifying critical path, activity throat, shortening project, precedence networks. Risk Management:
Introduction, the nature of risk, managing risk, risk identification, risk analysis, reducing the risks,
evaluating risks to the schedule, calculating the z values.

1. Software Testing: Principles and Practices by Naresh Chauhan
2. Software Project Management (2nd Edition), by Bob Hughes and Mike Cotterell, 1999, TMH
3. Software Engineering – A Practitioner’s approach, Roger S. Pressman (5th ed), 2001, MGH
4. Software Project Management, Walker Royce, 1998, Addison Wesley.
5. Managing Global software Projects, Ramesh, 2001, TMH.
6. Gill, Nasib Singh: Software Engineering, Khanna Book Publishing Company(Private) Limited,
New Delhi.
SOCIAL NETWORK ANALYSIS
Semester VI
Course code
Category PEC
Course title SOCIAL NETWORK ANALYSIS
Credits 3 0 0 3
Class work 30 Marks
Exam 70 Marks
Total 100 Marks
Duration of
03 Hours
Exam
COURSE OBJECTIVES:
This course covers data analysis on social networks, focusing on ways to handle large-scale
networks efficiently. It provides the main theoretical results in social network mining as well
as hands-on practice on key issues in the area.
COURSE OUTCOMES:
By completing the course, the students will be able to:
CO1. understand the basic concepts of social networks
CO2. understand the fundamental concepts in analyzing the large-scale data that are derived
from social networks
CO3. implement mining algorithms for social networks
CO4. perform mining on large social networks and illustrate the results.
CO5. Applying the concepts of social network on various web applications and analyze the
trend of interactions
UNIT-I
INTRODUCTION TO SOCIAL NETWORK MINING, GRAPH MODELS AND NODE METRICS:
Introduction to social network mining. Illustration of various social network mining tasks with real-
world examples. Data characteristics unique to these settings and potential biases due to them, Social
Networks as Graphs, Random graph models/ graph generators, power law, preferential attachment,
small world, stochastic block models, degree distributions. Models of evolving networks, Node based
metrics, ranking algorithms (Pagerank), Gephi graph visualization and exploration software –
practice.
UNIT-II
SOCIAL-NETWORK GRAPH ANALYSIS
Social network exploration/ processing: graph kernels, graph classification, clustering of social-
network graphs, centrality measures, community detection and mining, degeneracy (outlier detection
and centrality), partitioning of graphs.
UNIT-III
SOCIAL-NETWORK GRAPH ANALYSIS AND PROPERTIES
Social network exploration/ processing and properties: Finding overlapping communities, similarity
between graph nodes, counting triangles in graphs, neighborhood properties of graphs.
UNIT-IV
INFORMATION DIFFUSION IN SOCIAL NETWORKS
Strategic network formation: game theoretic models for network creation/ user behavior in social
networks. Information diffusion in graphs: Cascading behavior, spreading, epidemics, heterogeneous
social network mining, influence maximization, outbreak detection. Opinion analysis on social
networks: Contagion, opinion formation, coordination and cooperation, Dynamic Social Networks,
Applications and Research Trends: Dynamic social networks, Link prediction, Social learning on
networks, Special issues in Information and Biological networks, Important applications of social
network mining related to the above topics. Research trends.

1. David Easley and Jon Kleinberg, Networks, crowds, and markets, Cambridge
University Press, 2010.
2. Jure Leskovec, Anand Rajaraman and Jeffrey David Ullman, Mining of massive
datasets, Cambridge University Press, 2014.
CRYPTOCURRENCY WITH ETHEREUM
Semester VI
Course code
Category Professional Elective Courses
Course title Cryptocurrency With Ethereum
3 0 0 3
Classwork 30 Marks
Exam 70 Marks
Total 100 Marks
COURSE OBJECTIVES:
1. To introduce the concepts of cryptocurrency.
2. To understand working of Bitcoin and Ethereum
3. To study the security issues and safeguards related to bitcoin trading
4. To study governing cryptocurrency regulations and its impact on economy.
COURSE OUTCOMES:
CO1: Cryptocurrency: Bitcoin and Ethereum
CO2: Building efficient blockchain models to carry out tasks with the practical approach.
CO3: Evaluating the use and risks involved with cryptocurrency
CO4: Learning Smart contracts and their implications
UNIT - I
CRYPTOCURRENCY: History, Distributed Ledger Technology (DLT), cryptocurrency in blockchain,
Cryptographic basics for cryptocurrency: overview of Hashing, signature schemes, encryption schemes
and elliptic curve cryptography.
UNIT - II
BITCOIN: Creation of coins, Wallet, Genesis Block, Merkel Tree, Bitcoin Scripts, Bitcoin P2P
Network, hardness of mining, Transaction in Bitcoin Network, transaction verifiability, anonymity,
forks, payments and double spending, Consensus in a Bitcoin network, mathematical analysis of
properties of Bitcoin, Bitcoin protocols – Bitcoin Mining strategy and rewards, life of a Bitcoin Miner,
Mining Difficulty, Mining Pool.
UNIT - III
ETHEREUM: Ethereum Virtual Machine (EVM), Wallets for Ethereum, Ethereum Programming
Language: Solidity, Smart Contracts, The turing completeness of smart contract languages, attacks on
smart contracts, Ethereum Construction, DAO, GHOST, Vulnerability, Attacks, Sidechain: another
type of blockchain, Namecoin
UNIT - IV
CRYPTOCURRENCY REGULATION: Stakeholders, Roots of Bitcoin, Bitcoin scripting vs Ethereum
smart contracts, Legal Aspects - Cryptocurrency Exchange, Black Market and Global Economy,
Global Acceptability perspective.
1. Bitcoin and Cryptocurrency Technologies: A Comprehensive Introduction by Arvind
Narayanan, Joseph Bonneau, Edward Felten, Andrew Miller and Steven Goldfeder, Princeton
University Press (July 19, 2016).
2. Mastering Bitcoin: Unlocking Digital Cryptocurrencies by Antonopoulos
3. Bitcoin: A Peer-to-Peer Electronic Cash System by Satoshi Nakamoto
4. ETHEREUM: A Secure Decentralized Transaction Ledger by Gavin Wood, Yellow paper.2014.
5. A survey of attacks on Ethereum smart contracts by Nicola Atzei, Massimo Bartoletti, and
Tiziana Cimoli
7
TH
(Cyber Security)
Semester VII
L T P al
1 PCC Text and Web 3 0 0 3 30 70 100
Intelligence
2 LC Text and Web 0 0 2 1 50 50 100
Intelligence (P)
3 PCC Digital Forensics 3 0 0 3 30 70 100
4 PEC Professional 3 0 0 3 30 70 100
Elective-IV
5 OEC Open Elective-III 3 0 0 3 30 70 100
6 OEC Open Elective-IV 3 0 0 3 30 70 100
7 Project Project-II 0 0 8 4 100 100 200
8 Training Practical Training-II 0 0 2 1 50 50 100
Total 15 0 12 21 900
NOTE:
1. The evaluation of Practical Training - II will be based on the seminar, viva voice, and report
submitted by the students. According to performance, the students are awarded grades A, B, C, F.
A student who is awarded an ‘F’ grade is required to repeat Practical Training.
A Excellent
B Good
C Satisfactory
F Not
Satisfactory
2. Choose any one from Professional Elective Course – IV
3. Choose any one from Open Elective Course – III and IV *
Professional Elective Course – IV
1. Ethical Hacking
2. Information Security Risk Assessment
3. Wireless and Mobile security
4. Wireless sensor networks
Open Elective Course – III & IV: To be chosen from the bucket of Open Elective-III & IV
TEXT AND WEB INTELLIGENCE
Semester VII
Course code
Course title Text and Web Intelligence
3 0 0 3
Classwork 30 Marks
Exam 70 Marks
Total 100 Marks
COURSE OBJECTIVES:
1. Understand the fundamentals of information retrieval systems and its technologies
2. Process structured and unstructured data
3. Mining text and learning different analyzing techniques
4. Learning different techniques for textual and nontextual data
COURSE OUTCOMES:
CO1. To understand the concepts of Boolean retrieval utilized in Information retrieval system and acquire
the ability to Process Unstructured Data.
CO2. To get an overview of text mining and analytics with different techniques of finding similarity.
CO3. To comprehend the building and evaluation of Supervised and Unsupervised Categorization
Models.
CO4. To analyse the concepts of opinion and sentiment analysis
CO5. To apply the techniques for joint mining textual and non-textual data.
UNIT - I
INTRODUCTION AND DATA PREPROCESSING:
Introduction to the course, Introduction with example of Information retrieval problem, Boolean
Retrieval (Term Incidence Matrix, Inverted Index, Dictionary-Postings list, Processing Boolean Queries,
Skip Pointers), Preprocessing steps (Tokenization, stop word removal, normalization, stemming,
lemmatization, part of speech tagging), wildcard queries
UNIT - II
OVERVIEW OF TEXT MINING AND ANALYTICS:
Overview of Text Mining and Analytics, Paradigmatic Relation Discovery, syntagmatic relation
discovery, cosine similarity, tf-idf calculation, PLSA, LDA
UNIT - III
SENTIMENT ANALYSIS AND OPINION MINING:
Introduction to Sentiment Analysis, sentiment classification, opinion mining. Python NLTK Sentiment
Analysis, Recommendation Systems and its working
UNIT - IV
CASCADING AND DIFFUSION IN NETWORKS:
Introduction to web Analytics, Web mining process and techniques- data collection, web scraping,
Ranking Techniques: Page Rank and HITS

1. Christopher D. Manning, Prabhakar Raghavan and Hinrich Schutze, Introduction to Information
Retrieval, Cambridge University Press, 2008
2. Tony Ojeda, Rebecca Bilbro, Benjamin Bengfort, Applied Text Analysis with Python, O’Reilly
Media, June 2018.
3. Web Analytics for dummies, by Pedro Sostr and Jennifer LeClaire, Wiley Publishing, Inc.
4. Ashok N. Shrivastva, Mehran Sahami, Text Mining: Classification, Clustering and Applications; CRC
Press, edition 2010.
DIGITAL FORENSICS
Semester VII
Course code
Course title Digital Forensics
3 0 0 3
Classwork 30 Marks
Exam 70 Marks
Total 100 Marks
COURSE OBJECTIVES:
1. To understand the basic digital forensics and techniques for conducting the forensic examination
on different digital devices.
2. To understand how to examine digital evidences such as the data acquisition, identification analysis
COURSE OUTCOMES:
CO1. To apply forensic analysis tools to recover important evidence for identifying computer crime.
CO2. To be well-trained as next-generation computer crime investigators.
CO3. To collect forensics data and analyze them
CO4. To validate and test forensic tools on real-life data
CO5. To understand wireless and mobile forensic techniques
UNIT - I
COMPUTER FORENSICS FUNDAMENTALS:
What is Computer Forensics?, Use of Computer Forensics in Law Enforecement, Computer Forensics
Assistance to Human Recources/Employment Proceedings, Computer Forensics Services, Benefits of
professional Forensics Methodology, Steps taken by Computer Forensics Specialists. Types of Computer
Forensics Technology: - Types of Business Computer Forensic Technology. Types of Military Computer
Forensic Technology, Types of Law Enforcement- Computer Forensic Technology, Types of Business
Computer Forensic Technology. Computer Forensics Evidence and capture: Data Recovery Defined-
Data Back-up and Recovery-The Role of Back -up in Data Recovery-The Data -Recovery Solution.
UNIT - II
EVIDENCE COLLECTION AND DATA SEIZURE:
Why Collect Evidence? Collection Options, Obstacles-Types of Evidence-The Rules of Evidence-
Volatile Evidence-General Procedure-Collection and Archiving-Methods of Collections-Art facts-
Collection Steps -Controlling Contamination: The chain of custody. Duplication and Preservation of
Digital Evidence: Preserving the Digital Crime Scene-Computer Evidence processing steps-Legal
Aspects of collecting and Preserving Computer forensic Evidence. Computer image Verification and
Authentication: Special needs of Evidential Authentication - Practical Consideration-Practical
Implementation.
UNIT - III
COMPUTER FORENSIC ANALYSIS AND VALIDATION:
Determining what data to collect and analyze, validating forensic data, addressing data-hiding
techniques, performing remote acquisitions Network Forensics: Network forensic overview, performing
live acquisitions, developing standard procedures for network forensics, using network tools, examining
the honeynet project. Processing crime at incident scenes: Identifying digital evidence, collecting
evidence in private-sector incident scenes, processing law enforcement crime scenes, preparing for a
search, securing a computer incident or crime scene, seizing digital evidence at the scene, storing digital
evidence, obtaining a digital hash, reviewing a case.
UNIT - IV
CURRENT COMPUTER FORENSIC TOOLS:
Evaluating computer forensic tool needs, computer forensic software tools, computer forensic hardware
tools, validating and testing forensic software. E-mail investigations: Exploring the role of email in
investigations, exploring the role of client and server in email, investigating email crimes and violations,
understanding email servers, using specialized email forensic tools. Cell phone and mobile device
forensics: Understanding mobile device forensic, understanding acquisition procedures for cell phones
and mobile devices.

1. Computer Forensics, Computer Crime Investigation by John R, Vacca, Firewall Media, New Delhi.
2. Computer Forensics and Investigations by Nelson, Phillips Enfinger, Steuart, CENGAGE Learning.
3. Real Digital Forensics by Keith j. Jones, Richard Bejitlich, Curtis W. Rose,Addison Wesley Pearson
Education
4. Forensic Compiling, A Tractitioner is Guide by Tony Sammes and Brain Jenkinson, Springer
International edition.
5. Computer Evidence Collection &Presentation by Chrostopher L.T. Brown, Firewall Media.
6. Homeland Security, Techniques & Technologies by Jesus Mena, Firewall Media.
7. Software Forensics Collecting Evidence from the Scene of a Digital Crime by Robert M. Slade ,TMH
2005
8. Windows Forensics by chad Steel, Wiley India Edition.
TEXT AND WEB INTELLIGENCE LAB
Semester VII
Course code
Course title Text and Web Intelligence Lab
0 0 2 1
Classwork 50 Marks
Exam 50 Marks
Total 100 Marks
COURSE OUTCOMES:
CO1. Apply the basic concepts of Web mining using NLTK
CO2. Utilizing regular expression to retrieve and mining information
CO3. To understand and apply different stemming and lemmatization techniques
CO4. To capture and contrast different clustering methodologies
CO5. To work on HTML markups
EXPERIMENTS
1. Consider the input string - “Joe waited for the train. The train was late. Mary and Samantha took the
bus. I looked for Mary and Samantha at the bus station.”
• Write a Python NLTK program to split the text sentence/paragraph into a list of words.
• Write a Python NLTK program to create a list of words from a given string. Consider same input
as in the previous question.
• Write a Python NLTK program to split all punctuation into separate tokens.
2. Write a Python NLTK program to tokenize words, sentence wise.
3. Write a Python NLTK program to remove Twitter username handles from a given twitter
text. Consider input string as: "@abcd @pqrsNoSQL introduction - w3resource
http://bit.ly/1ngHC5F #nosql #database #webdev".
4. Write a Python NLTK program to find parenthesized expressions in a given string and divide
the string into a sequence of substrings.
5. Use PorterStemmer() to perform Stemming on the list. Input = ["program", "programs",
"programer", "programing", "programers"]
6. Apply SnowballStemmer on the previous input.
7. Perform lemmatization on the list. Input = ["program", "programs", "programer", "programing",
"programers"]
8. Write a program to strip away HTML markup with the help of the BeautifulSoup library,
and use regular expressions to remove open and close double brackets and anything in
between them.
9. Write a program to Normalize the data and remove non-ASCII characters from a list of
normalized tokens.
10. Write a program to remove accented characters
PRACTICAL TRAINING - II
Semester VII
Course code
Course title Practical Training - II
0 0 1 1
Internal Assessment 50
External Assessment 50
Total 100
Duration of Exam -
The evaluation of Practical Training - II will be based on the seminar, viva voice, and report
submitted by the students. According to performance, the students are awarded grades A, B, C, F. A
student who is awarded an ‘F’ grade is required to repeat Practical Training.
A Excellent
B Good
C Satisfactory
F Not Satisfactory
PROJECT - II
Semester VII
Course code
Course title Project - II
0 0 6 3
Classwork 100 Marks
Exam 100 Marks
Total 200 Marks
COURSE OUTCOMES:
CO1. To prepare the student to gain major design and or research experience as applicable
to the profession
CO2. Apply knowledge and skills acquired through earlier coursework in the chosen project.
CO3. Make conversant with the codes, standards, application software and equipment
CO4. Carry out the projects within multiple design constraints
CO5. Incorporate multidisciplinary components
CO6. Acquire the skills of comprehensive report writing
Students will be assigned projects individually or in a group of not more than 3 students
depending on the efforts required for completion of project.
The project will have 4 stages:
(*Marks for internal evaluation are given in brackets)
1. Synopsis submission (10 marks)
2. 1st mid-term progress evaluation (10 marks)
3. 2nd mid-term progress evaluation (10 marks)
4. Final submission evaluation (20 marks)
The external examiner will evaluate the project based on idea/quality of project,
implementation of the project, project report and viva
Professional
Elective-IV
ETHICAL HACKING
Semester VII
Course code
Course title Ethical Hacking
3 0 0 3
Classwork 30 Marks
Exam 70 Marks
Total 100 Marks
COURSE OBJECTIVES:
1. The aim of the course is to introduce the methodologies and framework of ethical
hacking for enhancing the security.
2. The course includes-Impacts of Hacking; Types of Hackers; Information Security
Models; Information Security Program; Business Perspective; Planning a Controlled
Attack; Framework of Steps (Reconnaissance, Enumeration, Vulnerability Analysis,
Exploitation, Deliverable and Integration)
COURSE OUTCOMES:
CO1. To gain the knowledge of the use and availability of tools to support an ethical hack
CO2. To gain the knowledge of interpreting the results of a controlled attack
CO3. To understand the role of politics, inherent and imposed limitations and metrics for
planning of a test
CO4. To comprehend the dangers associated with penetration testing
CO5. To understand the concepts of reconnaissance and its applications
UNIT- I
INTRODUCTION: HACKING IMPACTS, THE HACKER:
Framework: Planning the test, Sound Operations, Reconnaissance, Enumeration, Vulnerability Analysis,
Exploitation, Final Analysis, Deliverable, Integration. Information Security Models: Computer Security,
Network Security, Service Security, Application Security, Security Architecture Information Security
Program: The Process of Information Security, Component Parts of Information Security Program, Risk
Analysis and Ethical Hacking.
UNIT - II
THE BUSINESS PERSPECTIVE: Business Objectives, Security Policy, Previous Test Results, Business
Challenges. Planning for a Controlled Attack: Inherent Limitations, Imposed Limitations, timing is
Everything, Attack Type, Source Point, Required Knowledge, Multi-Phased Attacks, Teaming and Attack
Structure, Engagement Planner, The Right Security Consultant, The Tester, Logistics, Intermediates, Law
Enforcement.
UNIT - III
PREPARING FOR A HACK: Technical Preparation, Managing the Engagement. Reconnaissance: Social
Engineering, Physical Security, Internet Reconnaissance.
UNIT - IV
ENUMERATION: Enumeration Techniques, Soft Objective, Looking Around or Attack, Elements of
Enumeration, Preparing for the Next Phase. Exploitation: Intutive Testing, Evasion, Threads and Groups,
Operating Systems, Password Crackers, RootKits, applications, Wardialing, Network, Services and Areas
of Concern.
1. James S. Tiller, “The Ethical Hack: A Framework for Business Value Penetration Testing”,
Auerbach Publications, CRC Press.
2. EC-Council, “Ethical Hacking and Countermeasures Attack Phases”, Cengage Learning.
3. Michael Simpson, Kent Backman, James Corley, “Hands-On Ethical Hacking and Network
Defense”, Cengage Learning.
INFORMATION SECURITY RISK ASSESSMENT
Semester VII
Course code
Course title Information Security Risk Assessment
3 0 0 3
Classwork 30 Marks
Exam 70 Marks
Total 100 Marks
COURSE OBJECTIVES:
1. To study different concepts of IT security and their management
2. To introduce the terminology, technology and its applications of IT security
3. To enable a clear understanding and knowledge of Security Analyst foundations
4. To introduce the tool, technologies and programming languages which is used in day to day
security analyst job role.
COURSE OUTCOMES:
CO1. Understanding the difference between Security Metrics and Audits.
CO2. Applying knowledge on Vulnerability Management
CO3. Analyzing the Information Security Audit Tasks, Reports and Post Auditing Actions
CO4. Understanding Information Security Assessments
CO5. Applying measures of physical and infrastructure security
UNIT-I
IT SECURITY MANAGEMENT AND RISK ASSESSMENT:
IT Security Management, Organizational Context and Security Policy, Security Risk Assessment,
Detailed Security Risk Analysis, Case Study: Silver Star Mines
UNIT-II
IT SECURITY CONTROLS, PLANS, AND PROCEDURES:
IT Security Management implementations, Security Controls or Safeguards, IT Security Plans,
Implementation of Controls, Monitoring Risks, Case Study: Silver Star Mines
UNIT-III
PHYSICAL AND INFRASTRUCTURE SECURITY:
Overview, Physical security Threats, Physical Security Prevention and Mitigation Measures,
Recovery from Physical Security Breaches, Integration of Physical and logical Security, Security
Awareness, training and Education, E-mail and Internet Use Policies, Computer Security Incident
Response Teams
UNIT-IV
SECURITY AUDITING:
Security Auditing Architecture, security Audit Trail, Implementing Logging Function, Audit Trail
Analysis, Example: An Integrated Approach.
1. Assessing Information Security (strategies, tactics, logic and framework) by A Vladimirov,
K.Gavrilenko, and A.Michajlowski
2. “The Art of Computer Virus Research and Defense by Peter Szor.”
3. https://www.sans.org/readingroom/whitepapers/threats/implementing-vulnerability-
management-process-34180
4. http://csrc.nist.gov/publications/nistpubs/800-40-Ver2/SP800-40v2.pdf
WIRELESS AND MOBILE SECURITY
Semester VII
Course code
Course title Wireless and Mobile Security
3 0 0 3
Classwork 30 Marks
Exam 70 Marks
Total 100 Marks
COURSE OBJECTIVES:
This skill oriented course equips the system Administrators with the skills required to protect
& recover the computer systems & networks from various security threats.
COURSE OUTCOMES:
By the end of the course Students will
CO1. Familiarize with the issues and technologies involved in designing a wireless and mobile
system that is robust against various attacks.
CO2. Gain knowledge and understanding of the various ways in which wireless networks can be
attacked and tradeoffs in protecting networks.
CO3. Have a broad knowledge of the state-of-the-art and open problems in wireless and mobile
security, thus enhancing their potential to do research or pursue a career in this rapidly
developing area.
CO4. Learn various security issues involved in cloud computing.
CO5. Learn various security issues related to GPRS and 3G.
UNIT-I
SECURITY ISSUES IN MOBILE COMMUNICATION: Mobile Communication History, Security –
Wired Vs Wireless, Security Issues in Wireless and Mobile Communications, Security
Requirements in Wireless and Mobile Communications, Security for Mobile Applications,
Advantages and Disadvantages of Application – level Security.
UNIT-II
SECURITY OF DEVICE, NETWORK, AND SERVER LEVELS: Mobile Devices Security
Requirements, Mobile Wireless network level Security, Server Level Security. Application Level
Security in Wireless Networks: Application of WLANs, Wireless Threats, Some Vulnerabilities and
Attach Methods over WLANs, Security for 1G Wi-Fi Applications, Security for 2G Wi-Fi
Applications, Recent Security Schemes for Wi-Fi Applications
UNIT-III
APPLICATION LEVEL SECURITY IN CELLULAR NETWORKS: Generations of Cellular
Networks, Security Issues and attacks in cellular networks, GSM Security for applications, GPRS
Security for applications, UMTS security for applications, 3G security for applications, Some of
Security and authentication Solutions.
UNIT-IV
APPLICATION LEVEL SECURITY IN MANETS: MANETs, Some applications of MANETs,
MANET Features, Security Challenges in MANETs, Security Attacks on MANETs, External
Threats for MANET applications, Internal threats for MANET Applications, Some of the Security
Solutions.
Ubiquitous Computing, Need for Novel Security Schemes for UC, Security Challenges for UC, and
Security Attacks on UC networks, Some of the security solutions for UC.
1. Pallapa Venkataram, Satish Babu: “Wireless and Mobile Network Security”, 1st Edition, Tata
McGraw Hill,2010.
2. Frank Adelstein, K.S.Gupta : “Fundamentals of Mobile and Pervasive Computing”, 1st Edition,
Tata McGraw Hill 2005.
3. Randall k. Nichols, Panos C. Lekkas : “Wireless Security Models, Threats and Solutions”, 1st
Edition, Tata McGraw Hill, 2006.
4. Bruce Potter and Bob Fleck : “802.11 Security” , 1st Edition, SPD, O’REILLY 2005.
5. James Kempf: “Guide to Wireless Network Security, Springer. Wireless Internet Security –
Architecture and Protocols”, 1st Edition, Cambridge University Press, 2008.
WIRELESS SENSOR NETWORKS
Semester VII
Course code
Course title Wireless Sensor Networks
3 0 0 3
Classwork 30 Marks
Exam 70 Marks
Total 100 Marks
COURSE OBJECTIVES:
1. To make students understand the basics of Wireless sensor Networks.
2. To familiarize with learning of the Architecture of WSN.
3. To understand the concepts of Networking and Networking in WSN.
4. To study the design consideration of topology control and solution to the various
problems.
5. To introduce the hardware and software platforms and tool in WSN
COURSE OUTCOMES:
CO1. By the end of the course Students will be able to:
CO2. Understand challenges and technologies for wireless networks
CO3. Understand architecture and sensors
CO4. Describe the communication, energy efficiency, computing, storage and transmission
CO5. Establishing infrastructure and simulations
CO6. Explain the concept of programming the in WSN environment
UNIT – I
OVERVIEW OF WIRELESS SENSOR NETWORKS:
SingleNode Architecture Hardware Components Network Characteristics unique constraints
and challenges, Enabling Technologies for Wireless Sensor Networks Types of wireless sensor
networks.
UNIT – II
ARCHITECTURES:
Network Architecture Sensor Networks Scenarios Design Principle, Physical Layer and
Transceiver Design Considerations, Optimization Goals and Figures of Merit, Gateway Concepts,
Operating Systems and Execution Environments introduction to Tiny OS and nesC Internet to
WSN Communication.
UNIT – III
NETWORKING SENSORS:
MAC Protocols for Wireless Sensor Networks, Low Duty Cycle Protocols And Wakeup Concepts
– SMAC, BMAC Protocol, IEEE 802.15.4 standard and ZigBee, the Mediation Device
Protocol, Wakeup Radio Concepts, Address and Name Management, Assignment of MAC
Addresses, Routing Protocols Energy Efficient Routing, Geographic Routing.
UNIT – IV
INFRASTRUCTURE ESTABLISHMENT:
Topology Control, Clustering, Time Synchronization, Localization and Positioning, Sensor
Tasking and Control.
TEXT AND REFERENCES BOOKS:

1. Holger Karl & Andreas Willig, "Protocols And Architectures for Wireless Sensor
Networks", John Wiley, 2005.
2. Feng Zhao & Leonidas J.Guibas, “Wireless Sensor Networks An Information
Processing Approach", Elsevier, 2007.
3. Waltenegus Dargie , Christian Poellabauer, “Fundamentals of Wireless Sensor Networks
Theory and Practice”, John Wiley & Sons Publications, 2011
4. Kazem Sohraby, Daniel Minoli, & Taieb Znati, “Wireless Sensor NetworksTechnology,
Protocols, and Applications”, John Wiley, 2007.
5. Anna Hac, “Wireless Sensor Network Designs”, John Wiley, 2003
8
th
(Cyber Security)
Semester VIII
S. Category Course Course Title Hours per Credits Marks Marks for Total
No Code week for End Term
L T P
al n
1 PCC MOOC-1 3 0 0 3 30 70 100

2 PCC MOOC-2 3 0 0 3 30 70 100
3 PROJ Project III/Industrial 0 0 16 8 150 150 300
Project
Total 06 16 14 210 290 500
PROJECT – III
Semester VIII
Course code
Course title Project - III
0 0 20 10
Classwork 150 Marks
Practical 150 Marks
Total 300 Marks
COURSE OBJECTIVES:
1. To prepare the student to gain major design and or research experience as applicable
to the profession
2. Apply knowledge and skills acquired through earlier coursework in the chosen project.
3. Make conversant with the codes, standards, application software and equipment
4. Carry out the projects within multiple design constraints
5. Incorporate multidisciplinary components
6. Acquire the skills of comprehensive report writing
Students will be assigned projects individually or in a group of not more than 3

students depending on the efforts required for completion of project.
The project will have 4 stages:
(*Marks for internal evaluation are given in brackets)
1. Synopsis submission (10 marks)
2. 1st mid-term progress evaluation (10 marks)
3. 2nd mid-term progress evaluation (10 marks)
4. Final submission evaluation (20 marks)
The external examiner will evaluate the project based on idea/quality of project,
implementation of the project, project report and viva.
MOOC - I
Semester VIII
Course code
Course title MOOC - I
3 0 0 3
Classwork -
Practical -
Total 100 Marks
Duration of Exam -
A student has to complete NPTEL Courses of 12 Weeks respectively through MOOCs. For
registration to MOOCs Courses, the students shall follow NPTEL Site http://nptel.ac.in/ as per
the NPTEL policy and norms. The students can register for these courses through NPTEL
directly as per the course offering in Odd/Even Semesters at NPTEL. These NPTEL courses
(recommended by the University) may be cleared during the B. Tech degree program (not
necessary one course in each semester). After successful completion of these MOOCS courses
the students, shall, provide their successful completion NPTEL status/certificates to the
University (COE) through their college of study only.
MOOC - II
Semester VIII
Course code
Course title MOOC - II
3 0 0 3
Classwork -
Practical -
Total 100 Marks
Duration of Exam -
A student has to complete NPTEL Courses of 12 Weeks respectively through MOOCs. For
registration to MOOCs Courses, the students shall follow NPTEL Site http://nptel.ac.in/ as per
the NPTEL policy and norms. The students can register for these courses through NPTEL
directly as per the course offering in Odd/Even Semesters at NPTEL. These NPTEL courses
(recommended by the University) may be cleared during the B. Tech degree program (not
necessary one course in each semester). After successful completion of these MOOCS courses
the students, shall, provide their successful completion NPTEL status/certificates to the
University (COE) through their college of study only.
Chapter 4 Guidelines for Assessment
of Theory Courses
Assessment tools for theory courses
The overall direct and indirect tools of assessment for theory courses are given below.
Assessment Tools for Theory Courses

Direct Tools
Sr No. Description of the tool COs Covered
1 Questions must cover at least first three Levels of COs.
Sessional Examination I (Remember, Understand, Apply)
2 Questions must cover at least four Levels of

Sessional Examination II COs including the first three levels (Remember, Understand,
Apply).
3 Internal Examination III Last four levels of COs
(Open Book Mode) (Apply, Analyse, Evaluate, Create)
4 Last Three Levels of COs
Assignment I
(Analyse, Evaluate, Create)
6 Last Two Levels of COs (Evaluate and Create)
Assignment II
7. Attendance/Level of Learning Curve and Communication
Participation in Class
8. Final Examination Possibly Covering all levels of COs
Indirect Tools
1. End-Semester Survey Covering all levels of COs
2. Exit Survey Covering all POs
Guidelines for internal evaluation

1. All the teachers are required to set questions sessional/minor exams according to the COs and the level of CO
needs to be mentioned against each question.
2. The three minor examinations together must cover all the levels of COs.
3. It is compulsory to give two assignments during the semester pertaining to the last three levels of COs.
4. The sessional/minor examination answer sheet must be evaluated as per the COs.
5. All the teachers are required to maintain the internal evaluation record according the COs
6. All the teachers are required to submit the internal evaluation record along with the computation of attainment
levels of COs.
7. The respective proformas for making sessional/ minor question papers, maintaining CO-wise evaluation record of
the course and submitting the CO attainment levels are given next in this chapter.
8. For the purpose of internal assessment, the average of the highest marks obtained by a student in any of the two
minor examinations will be considered. Class Performance will be measured through percentage of lectures
attended (4 marks) Assignments (4 marks) and class performance (2 marks).
Department of Computer Science and Engineering
Gurugram University, Gurugram-122018
Sample Detailed Direct Tools for Internal Assessment
The sessional exams must contain four questions.
Question No. Question No. 1 Question No. 2 Question No. 3 Question No. 4
Any of these levels
Levels of
First level: Second level: Third Level: (3, 4, 5)
Sessional 1 Bloom’s
Remember Understand Apply Apply, Analyse,
Taxonomy
Evaluate
Marks
4 4 6 6
Distribution
No. of
Question No. 1 Question No. 2 Question No. 3 Question No. 4
Questions
Any of these
Levels of
First level: Second level: Third Level: levels: (4, 5, 6)
Sessional 2 Bloom’s
Remember Understand Apply Analyse, Evaluate,
Taxonomy
Create
Marks
4 4 6 6
Distribution
No. of
Question No. 1 Question No. 2 Question No. 3 Question No. 4
Questions
Any one out of
Any one out
Levels of fourth and fifth
Third level: fifth and sixth Last level:
Internal Examination Bloom’s levels:
Apply levels: Create
Taxonomy Analyse,
Evaluate
Evaluate
Marks
4 4 6 6
Distribution
Must be based on the last three levels
Assignment 1
For purpose of computing CO attainment level only (10 Marks)
Must be based on the last two levels
Assignment 2
For purpose of computing CO attainment level only (10 Marks)
Industrial Training Based on the last four levels
Industrial Training/Mini Based on the last four levels
Project
Major Project Based on the last four levels
Note: The course coordinator may make slight modification in the style of minor examinations
as per the requirement the course. The due weightage to higher level COs must be maintained in all
respects.
Record of CO-wise Internal Assessment
Name of the Programme: Semester:
Nomenclature of the Course: Course Code:
Details of Students Minor I Minor II Minor 3 AI AII Overall Attainment
(CO5) (CO6)
Roll. No. Name Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 - Q1 Q2 Q3 Q4
- -
CO1 CO2 CO3 CO4 CO1 CO2 CO3 CO4 CO5 C03 CO4 CO5 CO6 CO1 CO2 CO3 CO4 CO5
CO5 CO6
4 4 6 6 4 4 6 6 6 4 4 6 6 10 10
7/8 6/8 12/16 6/110 4/6
101 - 3 3 4 4 - 4 3 5 4 3 2 4 3 5 4
0.85 0.80 0.75 0.73 0.77
102 - - - - - -
103 - - - - - -
104 - - - - - -
% student getting
more than 55 % 0.82 0.78 0.72 0.65 0.60
marks
Attainment 3 3 3 2 1
Levels
Name of the Course Coordinator Signature of the Course Coordinator
Max marks for COs: CO1:8; CO: 8; CO3=16; CO4=10; CO5=22, CO6=16.
Criteria for Computing Attainment Level
Attainment Level - (None): Below 60% of students score more than 55% marks out of the maximum relevant marks.
Attainment Level 1 (low): 60% of students score more than 55% marks out of the maximum relevant marks.
Attainment Level 2 (Medium): 70% of students score more than 55% marks out of the maximum relevant marks.
Attainment Level 3 (high): 80% of students score more than 55% marks out of the maximum relevant.
Scheme and Curriculum for UG Degree Course (B.Tech.) in Computer Science and Engineering (Cyber Security)
Sample Overall Attainment Level of COs for Data Structures and Algorithms Course
List of Course Outcomes Level of attainment

3
CO1. list or describe types of data structures and
operations that can be implemented on these data
structures.
CO2. Demonstrate the use of various data structure and 3
their related operations
CO3. Apply appropriate data structures with respect to 3
effective storage of data and efficiency of the required
operations on data for solving real world problems.
2
CO4. Analyse the time complexity of searching and
algorithms.
1
CO5. formulate data structures and prescribe operations for
given real world situations.
Note: The class coordinators need to submit the course outcome attainment levels as given in the table
above.
Chapter 5: Guidelines
Internal and external
Assessment of Lab. Courses
Assessment Tools for Lab. Courses
The assessment tools for evaluating lab. courses are given below. The total lab evaluation marks:
100 (Internal: 50; External 50)
Assessment Tools for Lab. Courses
Direct Tools
Sr Description of the tool COs Covered
No.
1 Assignments 10 to 15 assignments based on the
last four levels of COs
(Apply, Analyse, Evaluate, Create)
2. Group Assignment (s) Last three levels of COs
(Analyse, Evaluate, Create)
3. Laboratory Evaluations (MLE) I and II (Each of 50 marks) Last four levels of COs
(implementing a problem, lab. record, VIVA-VOCE, (Apply, Analyse, Evaluate, Create)
use of ethical practices, self-learning and group spirit
4. External Examination (50 Marks) Last four levels of COs
(implementing a problem, lab. record, VIVA-VOCE, use of (Apply, Analyse, Evaluate, Create)
ethical practices
Indirect Tools
1. End-Semester Survey Covering all levels of COs
2. Exit Survey Covering all POs
Guidelines for internal and external evaluation of lab. courses:

1. The internal evaluation MEA I and MEA II will be conducted in the week before or after the internal minor
examinations for the theory courses by the course coordinator.
2. The course coordinator will conduct these minor evaluations in the slots assigned to them as per their
timetable.
3. The Chairperson of the Department will only notify the week for the internal laboratory course evaluations.
4. The marks for MLE I and MLE II must be submitted within a week of the conduct of these laboratory
course evaluations.
5. The overall internal marks will be calculated as the average of the two minor laboratory course evaluations.
6. The internal lab practical examination is to be conducted strictly on the pattern of external practical
examination.
7. The evaluation must be conducted to measure the attainment level of COs
8. The proforma for break-up of marks for internal and external lab. course evaluations are given next in this
chapter.
9. The external examination will be conducted by external examiner appointed by the Controller of Examination
along with the internal examiner, preferably the laboratory course coordinator, appointed by the Chairperson
of the Department.
10. For implementing the spirit of continuous evaluation, the course coordinators will maintain the experiment-
wise record of the performance of students for the laboratory courses as a part of their lab course file.
11. The course coordinator/Internal Examiners/External Examiners will maintain and submit the bifurcation of
marks obtained by the students in internal as well as external evaluations in the prescribed proformas to the
respective departments in addition to submitting and uploading of overall marks on the university portal as
per the requirement of the result branch.
12. The laboratory course coordinator will also conduct laboratory course exit survey and, compute and submit
the attainment levels of the course outcomes of the laboratory course based on direct and indirect evaluation
components and submit it to the Chairperson office along with the internal assessment marks.
Internal Laboratory Course Evaluation Proforma
Laboratory Course Evaluation-I (LE-I) / Laboratory Course Evaluation-II (LE-II)
Name of the Programme:
Semester:
Nomenclature of the Course:
Course Code:
SR. No. Roll. No. Written work Laboratory Class Total
and/or conduct (VIVA-VOCE) Record/ Performance
of based on laboratory course File. (Attendance/
experiment(s) outcomes Ethical practices
from CO2 to CO4 followed, Self-
Learning and
Team Spirit)
CO1 CO2 CO3 CO4 CO5 CO6 50
1
2
3
.
.
Total No. of Students Present: Absent
Name of the Course Coordinator Signature of the Course Coordinator

Note: The CO-wise weightage be decided as per the requirement of the Lab Course by the Course Coordinator
in consultation with the Chairperson.
External Laboratory Course Evaluation Proforma
Nomenclature of the Course:
Course Code:
Name of the Internal Examiner:
Name of the External Examiner:
SR. No. Roll. No. Written work (VIVA-VOCE) Laboratory Total Marks
and /or Conduct of (20) Record/File (50)
Experiment(s)
(20) (10)
1
2
3
.
Total No. of Students: Present: Absent:
Name and signature of the Internal Examiner Name and signature of the External Examiner
Chapter 6: Evaluating Training and
Project Reports
Evaluation of Industrial Training/Internship
It is mandatory for all the students to go for industrial training or internship after fourth
semester and sixth semester. The students’ internship work is evaluated as per the
criteria given in the evaluation proforma given below.

Name of the Credits:

Programme:
Total Marks:
Semester: 100
Session:
Evaluation of Industrial Training (INT-CSE301)

SR. Roll. Significance and Knowled Judgement of Qualit Level Tota
No. No. originality of the ge of the the skill learnt y of of l
problem addressed problem and system Repor ethics 100
and the solution domain developed t followe
provided and the Writin d
tool used CO4 g
CO1+CO2 (VIVA- (20) CO6
(20) VOCE) CO5 (15)
CO3 (20)
(25)
1
2
3
.
.
Total Candidates:
Name (s) and Signature of the Internal/External
Examiner(s): No. of Candidates Present:
No. of Candidates Absent:
Date:
Name and Signature of the Chairperson
Guidelines for Preparing Industrial Training (Code ) Report
All the students are required to follow these guidelines for preparing their industrial training report.
General Guidelines
1. The industrial training report must include a declaration by the student that he/she has followed ethical practices
while doing the industrial training work. Any violation of ethical practices will lead to rejection of the industrial
training report. For instance, a plagiarized report or a readymade report purchased from market will be rejected
straight away.
2. Industrial training work carried out in groups of two students must include the individual contribution of the
students.
3. The industrial training report must be submitted to the internal guide in soft binding at least 7 days before the final
submission so that he/she can suggest changes.
Formatting Instructions
The formatting instructions are given in Table below.
Formatting Instructions
Sr. No. Item Formatting
1. No. of pages Minimum 20 and maximum 40
2. Paper size A4
3. Font Type Times New Roman
4. Normal text size 12
5. Page numbering Place: Centre Bottom
Type: Front material in Roman numbers
6. Margins Left margin: 3.75 cms (1.5 inch)
Right, bottom, top= 2.5 cms (1 inch)
7. References/Bibliography IEEE format
8. Binding soft binding of good quality
Contents of the Industrial Training Report
The contents of the industrial training report should be organised as described below.
1. Declaration that the students has carried out his work on his own. It is his/her original creation, not
plagiarised from any other source and due credit has been given to the source material used in the
industrial training report through references and citations.
2. Acknowledgement
3. List of figures
4. List of Tables
5. List of Abbreviations
6. Contents
Contents in the Body of the industrial training report
The report must be written in English. The ideas must be organised in a clear and concise fashion.
S. No Content Tentative No. of

pages
1. Profile of the Company At most 2 pages
2. Introduction 4-5 pages
3. Description of skills learned 6-10 pages
4. Application developed (if any) based on skills learnt 20-40 pages
5. Scope of the training/ Application developed 2 paragraph
The industrial training report should not no way exceed 70 pages and should be
submitted in soft binding of good quality as per university norms.
Format of the title page

The format of the title page is given is given on next page.
TITLE OF THE INDUSTRIAL TRAINING REPORT
(Write in Times New Roman, 16-point size, Bold and Centred and Uppercase font)
Training report submitted to

Gurugram University, Gurugram for the partial award of the
degree
(Write in Times New Roman, 12-point size font, Bold, Italics and Centred style after 4
lines gap with 12 font size from the title of the project)
of
(Write in Times New Roman, 12-point size font, Bold, Italics and Centred style after
1 lines gap with 12 font size from the text above in three lines)
Bachelor of Technology
in Computer Science and Engineering
(Cyber Security)
(Write in Times New Roman, 14-point size, Bold, Centred style after “of” after 1 line gap
with 12 font size)
By
(Write in Times New Roman 12-point size, Bold, Italics, and Centred style after the
name of the degree with 1 line gap with 12 font size)
Your Name
(Enrolment Number)
(Write in Times New Roman, 14-point size font, Bold, Centred style after1 line gap
with 12 font from “By”)
Department of Computer Science & Engineering

GURUGRAM UNIVERSITY, GURUGRAM
Month, Year
(Write in Times New Roman, 14-point size font, Bold, Centred style, after 2 lines gap from logo)
Declaration to be submitted for training report
DECLARATION
I, Your Name, Your Roll No., certify that the work contained in this industrial training report is
original and has been carried by me in the ------------------ company name. This work has not been
submitted to any other institute for the award of any degree and I have followed the ethical
practices and other guidelines provided by the Department of Computer Science and Engineering
in preparing the industrial training report.
Signature
Name of Student
Registration Number
Signature
Supervisor/Mentor
Designation
Evaluation of mini-project
The proforma for evaluating the project using open source tools is given on the next page.
Gurugram University Gurugram

Gurugram University, Gurugram-
122018
Name of the Credits:
Programme:
Total Marks: 100
Semester
Session:
Evaluation of Industrial Training/Internship Report (Code)
Quality Level of
Knowledge of Knowledge of Quality of
Significance of the of the engagement with
SR. Roll. the problem the techniques the Report Total
problem addressed solution ethical practices
No. No.
CO1 (15)
domain and tools used
provided
Writing
and self- learning (100)
CO2 (15) CO3 (15) CO5 (20)
CO4 (20) CO6 (15)
1
2
3
.
.
Name of the examiner(s): Total Candidates:
Signature of the Examiner(s): No. of Candidates Present:
Date: No. of Candidates Absent:
Signature of Chairperson
Gurugram University Gurugram

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SCHEME AND CURRICULUM BOOK

DEPARTMENT OF COMPUTER SCIENCE AND ENGINEERING

Chapter 1: General Information

Chapter 5: Guidelines for Internal and External Assessment of Lab. Courses

2. To move up through international alliances and collaborative initiatives to achieve

3. To create rigorous academic and research environment for creation of knowledge

4. To attract and build people in a rewarding and inspiring environment by fostering

ABOUT THE PROGRAM

1. The scheme will be applicable from Academic Session 2022-23 onwards.

PROGRAM SPECIFIC OUTCOMES

SEMESTER-WISE SUMMARY OF THE PROGRAM

COURSE CODE AND DEFINITIONS

OPEN ELECTIVE COURSES (OEC)

4 ESC Basic of Electrical and 3 0 0 3 30 70 100

7 HSMC Communication Skills in 50 50 100

11 AU Sports (Audit Course) 0 0 0

Total 14 1 11 19.5 900

3 HSMC Human Value & Soft 30 70 100

6 PCC Object Oriented 30 70 100

2 PCC Introduction to 3 0 0 3 30 70 100

5 PCC Operating 3 0 0 3 30 70 100

9 LC Operating Systems (P) 0 0 2 1 50 50 100

10 BSC Aptitude Reasoning- I 3 0 0 3 30 70 100

Professional Elective Course – I

* Open Elective Course – I

Professional Elective Course – IV

4 ESC Basic of Electrical and 3 0 0 3 30 70 100

7 HSMC Communication Skills in 50 50 100

11 AU Sports (Audit Course) 0 0 0

Total 14 1 11 19.5 900

Course Code BSM-101

1. To develop logical understanding of the subject

Course code BSP-101

Course title Physics

Suggested reference books

1. Pierret, Semiconductor Device Fundamental,

Course code EEE-101

1. E. Huges, “Electrical Technology”, ELBS.

Suggested reference books

Course code CSE-101

Suggested Text Books:

Suggested Reference Books

1. To understand the basic concepts of environmental studies and natural resources.

Course code HSE-101P

Category Basic Science Course

Course title Physics (P)

Note: At least 8 experiments are to be performed by the students.

List of Subject related Experiments:

1. To study the forward and reverse characteristics of P-N junction diode.

Course code EEE-101P

Note: At least 8 experiments are to be performed by the students.

Course code CSE-101P

List of Subject related Experiments:

1. To formulate the algorithms for simple problems

Tutorial 1: Problem solving using computers:

Tutorial 2: Variable types and type conversions:

Tutorial 3: Branching and logical expressions:

Tutorial 4: Loops, while and for loops:

Tutorial 6: 2D arrays and Strings