Land Fraud Detection System.

PROJECT REPORT
Submitted by
ASWANI DAS (PEC17CS012)
ASWATHY AJITH (PEC17CS013)
NISY THERESA ANIL (PEC17CS026)
GAYATHRY A R (PEC17CS015)
to
the APJ Abdul Kalam Technological University
in partial fulfilment of the requirements for the award
of
the Degree of Bachelor of Technology
In
Computer Science and Engineering

Department of Computer Science and Engineering

College of Engineering Pathanapuram
ELIKKATTOOR PO, KOLLAM - 689696
June 2021
 Department of Computer Science and Engineering
College of Engineering Pathanapuram, Kollam

CERTIFICATE
This is to certify that the report entitled ’ Land Fraud Detec-
tion System’ submitted by Aswathy Ajith , Aswani Das,
Nisy Theresa Anil, Gayathry A R to the APJ Abdul Kalam
Technological University in partial fulfilment of the requirements
for the award of the Degree of Bachelor of Technology in Com-
puter Science and Engineering is a bonafide record of the seminar
work carried out by her under our guidance and supervision. This
report in any form has not been submitted to any other University
or Institute for any purpose.

Mrs.Jooby E
Mr.Siju Koshy Project Guide and
Project Coordinator Coordinator
Assistant Professor Assistant Professor
Dept. of CSE Dept. of CSE

Mrs.Jooby E
Assistant Professor
Head of the Department
Dept. of CSE
 Acknowledgement
Firstly , I would like to express our sincere gratitude and thanks
to Professor,Mr.Dr.Biju Kumar R,Principal of College of
Engineering Pathanapuram for providing us with a well equipped
laboratory and all other facilities.

I express my sincere gratitude to Mrs.Jooby E, Project Co-

ordinator and Guide , Head of the Department, Department of
Computer Science and Engineering, for the moral support and
guidance during the course of the work.

I express my sincere gratitude to Mr.Siju Koshy, Project Co-

ordinator, Department of Computer Science and Engineering, for
the valuable suggestions and advices during the course of the work.

I also like to thank Mr.Siju.Koshy my Class Tutor and I am

happy to thank other faculty members,technical and administra-
tive staff of the Department of Computer Science and Engineering
for their valuable support and heartfelt cooperation.I thank my
family and friends for giving me mental support and enabling me
to work efficiently. I also remember with regard my parents, for all
the help and moral support that they provided me for my seminar.
I express our gratitude to all other staff members and classmates
for their help and motivation.
ASWATHY AJITH
ASWANI DAS
NISY THERESA ANIL
GAYATHRY A R
 Declaration
We undersigned hereby declare that the project report ’Land Fraud De-
tection System’, submitted for partial fulfilment of the requirements for
the award of degree of Bachelor of Technology of the APJ Abdul Kalam
Technological University, Kerala is a bonafide work done by them under
supervision of Mrs.Jooby E. This submission represents our ideas in our
own words and where ideas or words of other have been included. We
have adequately and accurately cited and referenced the original sources.
We also declare that we have adhered to ethics of academics honesty and
integrity and have not misrepresented or fabricated any data or idea or
fact or source in our submission. We understand that any violation of the
above will be a cause for disciplinary action by the institute and/or the
University and can also evoke penal action from the sources which have
thus not been properly cited or from whom proper permission has not
been obtained. This report has not been previously formed the basis for
the award of any degree,diploma or similar title of any other University.

DATE :26-6-21

PLACE :PATHANAPURAM

ASWATHY AJITH

ASWANI DAS

NISY THERESA ANIL

GAYATHRY A R
 Abstract
Land frauds in Kerala have been identified as an important source of dam-
age to Kerala’s economic balance. As per the Kerala land reforms act,
1969 there is a maximum ceiling limit of land area a person can own. But
now a day’s people are purchasing lands illegally beyond this limit, to over-
come this here is a web application to detect these land frauds based on
the ration card number of each family which provide the list of members
in a family with the acres of land each member in the family owns and
since it require large amount of data for implementing this application ,
Big Data analytics is used which is the process of collecting, organizing
and analysing large sets of data (called Big Data) to discover patterns and
other useful information. Big Data cleans large amount of data efficiently
and removes redundancy. This application also includes cadastral map fea-
tures. Cadastral map is a technical term for a set of records showing the
extent, value and ownership (or other basis for use or occupancy) of land.
Strictly speaking, a cadastral map is a record of areas and values of land
and of landholders that originally was compiled for purposes of taxation.
This feature is implemented in such a way that it can be accessed by both
public and authorities whereas land fraud detection feature can only be ac-
cessed by authorities. The main technology used here is image processing.
Image processing is a method to perform some operations on an image, in
order to get an enhanced image or to extract some useful information from
it. It is a type of signal processing in which input is an image and output
may be image or characteristics/features associated with that image. This
cadastral feature provides the image of lands with its full details. This
cadastral feature can also be used to avoid land frauds.

iii
Contents

List of Figures vi

1 Introduction 1
1.1 General Background . . . . . . . . . . . . . . . . . . . . . 1
1.2 Objectives . . . . . . . . . . . . . . . . . . . . . . . . . . . 2
1.3 Scheme . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2
1.4 Organization of the report . . . . . . . . . . . . . . . . . . 2

2 Literature Review 3
2.1 Fraud detection and prevention by using big data analytics 3
2.2 Online land fraud detection and saftey the privacy . . . . 4
2.3 Online credit card fraud dtection: A hybrid framework with
big data technologies . . . . . . . . . . . . . . . . . . . . . 4
2.4 Big data analytics for detection of frauds in matrimonial
websites . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4

3 PROPOSED DESIGN 6
3.1 Problem statement . . . . . . . . . . . . . . . . . . . . . . 6
3.2 Formulation of Objective . . . . . . . . . . . . . . . . . . . 6

4 DESIGN 7
4.1 Architecture of the System . . . . . . . . . . . . . . . . . . 7
4.1.1 App logic . . . . . . . . . . . . . . . . . . . . . . . 9
4.2 Modules . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10

5 RESULT & ANALYSIS 12

iv
6 CONCLUSION 14

v
List of Figures

4.1 System Architecture . . . . . . . . . . . . . . . . . . . . . 8

4.2 Standard Acres Conversion Factors . . . . . . . . . . . . . 9
4.3 Modules . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11

5.1 Land Types . . . . . . . . . . . . . . . . . . . . . . . . . . 12

5.2 Standard acre values in south kerala vs north kerala . . . . 13

vi
Chapter 1

Introduction

1.1 General Background

India is a diverse geographical country comprising of 28 states, 8 union
territories, housing multi lingual residents, sheltering about 17.7 percent-
age of world’s population and having a total geographic area of 3,287,240
sq.km, wherein 91 percentage of the area is covered by land and remaining
by water. Ensuring proper land governance for such a huge geographical
area is indeed an act of great responsibility.
The Indian judiciary is already saddled with thousands of cases involv-
ing land frauds. A resolution, hence, does take time and involves spending
a lot of money in the form of lawyers and other fees. Land is characterised
by its ability of instant wealth generation, capable of being sold, mort-
gaged, gifted, inherited and bequeathed. With a surge in land registry
there has been an increased reporting of frauds in land registry.
As per the Kerala land reforms act, 1969 there is a maximum ceiling
limit of land area a person can own. But now a day’s people are purchasing
lands illegally beyond this limit. We propose a web application to detect
these land frauds based on the ration card number of each family which
provides us the list of members in a family with the acres of land each
member in the family owns. Since we need large amount of data for imple-
menting this application we use Big Data analytics. This application also
includes cadastral map features where it can be accessed by both public
and authorities whereas land fraud detection feature can only be accessed

1
by authorities.

1.2 Objectives
Main objective of the system is

• To detect Land Frauds in Kerala

• Discover cadestral map features

1.3 Scheme

Analysing the total amount of land owned by a particular user by

using ration card number.

Gives up-to-date news about changing and new laws related to land
that helps user to aware about it.

1.4 Organization of the report

This module generally deals with a brief introduction part of what the sem-
inar report is. Chapter 2 is the background which includes a detailed lit-
erature survey. Chapter 3 deals with the proposed system, which includes
the brief introduction about the proposed strategy. Chapter 4 comes with
the implementation and design phase.Finally, Chapter 5 deals with the
conclusion of the work.

2
Chapter 2

Literature Review

There are four papers related to this system is selected for literature re-
view.They are described below.

2.1 Fraud detection and prevention by us-

ing big data analytics
Fraud detection is finding actual or expected fraud which takes place in an
organization and in the retail market it is one of the challenging aspects.
Analyzing financial crimes related to fraudulent activities is difficult where
traditional data mining techniques fail to address all of them. Big data
analytics is used to identify an unusual pattern to detect and prevent fraud
in the retail sector. Various predictive analytics tools are used to handle
massive data and their pattern.The key idea of this paper is to detect
fraudulent activities with the help of bigdata. The architecture of the
system includes collection of data records from various sources and passing
it on to the bigdata framework which includes the computation of fraud
indications

3
2.2 Online land fraud detection and saftey
the privacy
Big data framework aims to help people detect unexpected activity on
their property. Solves: 1. Fraud detection 2. Fraud prevention 3. Fraud
reduction
Analysis of different fraud schemes to discover fraud patterns using
data mining techniques.Uses Naive Byes algorithm techniques.Application
of Hadoop methods to identify suspicious transactions in land records. Big
data facilitate the building of fraud detection models that can be integrated
with registration systems, and act as an alarm system.

2.3 Online credit card fraud dtection: A hy-

brid framework with big data technolo-
gies
This paper focus on designing an online credit card fraud detection frame-
work with big data technologies. Which, propose a hybrid framework
with Big Data technologies to solve performance challenges faced by on-
line CCFDS. We propose a credit card fraud detection workflow, which
can fuse different detection models to improve accuracy.We design a four-
layer framework which includes distributed storage layer, batch training
layer, key-value sharing layer and streaming detection layer.We implement
the framework with the latest big data technologies like Hadoop, Spark,
Storm, HBase, etc. With these technologies, we are able to handle the
burst amount of data and build a scalable and reliable system.

2.4 Big data analytics for detection of frauds

in matrimonial websites
Increase in the number of cyber duping cases in matrimonial web sites. In-
ternet based matrimonial service provider can’t go beyond a proper limit in
carrying out verifications. This paper focuses on role of big data analytics

4
in verifying whether the profile is genuine or not.

• Anomaly Detection

• Business Rules

• Database Searches

• Predictive modeling

5
Chapter 3

PROPOSED DESIGN

3.1 Problem statement

• Land frauds in Kerala have been identified as an important source of
damage to Kerala’s economic balance.

• So we propose a web application to detect land frauds based on the

ration card number of each family.

3.2 Formulation of Objective

• To use Big Data analytics to detect Land frauds in kerala by analysing
the database based Kerala Land Reforms act 1969.

• Using Image processing technology,digitalized Cadestral map is made

available to Public.

6
Chapter 4

DESIGN

4.1 Architecture of the System

The fig 3.1 depicts the system architecture of the proposed design.The
input data is collected from the users by the system. The frontend is
developed by using HTML,CSS and Javascipt.HTML provides the basic
structure of sites, which is enhanced and modified by other technologies
like CSS and JavaScript. CSS is used to control presentation, formatting,
and layout. JavaScript is used to control the behavior of different ele-
ments.The input data is transferred to the Backend which is developed
with Python Django. Django is an open-source python web framework
used for rapid development, pragmatic, maintainable, clean design, and
secures websites.The backend contains the app logic which is described in
section 4.1.1. It uses the Web Server Gateway Interface (WSGI) Apache,
which defines how a web server communicates with and makes requests
to a Python application.The Web Server Gateway Interface is a simple
calling convention for web servers to forward requests to web applications
or frameworks written in the Python programming language. The current
version of WSGI, version 1.0.1, is specified in Python Enhancement Pro-
posal 3333. The corresponding response is given to the frontend. MySQL
database is used in this system. The application is used for a wide range
of purposes, including data warehousing, e-commerce, and logging appli-
cations. The most common use for mySQL however, is for the purpose of
a web database.

7
Figure 4.1: System Architecture

8
 Figure 4.2: Standard Acres Conversion Factors

4.1.1 App logic

According to The Kerala Land Reforms Act, 1963 :

a) In case of an adult unmarried person or a family consisting of a

sole surviving member, five standard acres and the ceiling limit shall
not be less than six and more than seven-and-a-half acres.
b) For a family consisting of two or more but no more than five mem-
bers, 10 standard acres and the ceiling limit shall not be less than 12
and more than 15 acres.
c) If it’s a family consisting of more than five members, 10 standard
acres increased by one standard acre for each member in excess of
five, and the ceiling limit shall not be less than 12 and more than 20

9
 acres.
d) For any other person, other than a joint family, 10 standard acres
and the ceiling limit shall not be less than 12 and more than 15 acres.
e)For agriculture and industry purpose no limit.

In districts across kerala , there is a particular conversion factor for

each type of land. This factor is used to convert normal acres to standard
acres. The evaluation is done after converting the value of acre to standard
acres(Refer fig:4.2).

4.2 Modules
1.STAFF USER
Component: Land purchase eligibility checking system

Staff user performs two main functions of the system:

• Inputs the users Ration card number and the amount of land re-
quested.

• Views the result after validation of the input based on the applied
logic which is the Kerala Land reforms Act of 1963.

The system will allow the staff users to check and confirm the appli-
cant’s eligibility to proceed to the purchase of land.

The eligibility shall be confirmed based on the logic and validity of

the input data.

2.PUBLIC USER
Component: User Facing Website

Public user access the static information from the website such as land
laws and recent updates from revenue department and can also submit

10
 Figure 4.3: Modules

their queries.

The Cadastral map features can also be accessed by them.

A website with informational content and offering an option for the

users to submit their queries or concerns related to land and revenue sys-
tems are included in this module.

The major content types would be News, Static Information Content,

Latest Publications, Rules and Regulations and Contact Details.

11
Chapter 5

RESULT & ANALYSIS

To confirm the proper validation of our system , we have to analyze the

input and output pattern of different use cases.According to our app logic
,for a family with less than 5 people, the total ceiling limit of land is 10
Standard acres. Suppose User A(whose family already owns 3.24 standard
acres of land)is trying to buy 14 acres of land of TYPE C.The system checks
whether she is eligible to purchase this or not.After proper conversions and
checking it shows the accurate result that she is not eligible to purchase
this much hence she will exceed the limit. Similarly rest of the test cases
were checked and obtained accurate results. Hence eligibility checking and
fraud detection were successfully executed.
The graph shows the difference in value of land across Kerala. Each
of the blocks corresponds to one standard acre. It differs based on

Figure 5.1: Land Types

12
Figure 5.2: Standard acre values in south kerala vs north kerala

district and land type

13
Chapter 6

CONCLUSION

The Indian judiciary is already saddled with thousands of cases involving

land frauds. A resolution, hence, does take time and involves spending a
lot of money in the form of lawyers and other fees. Land is characterised by
its ability of instant wealth generation, capable of being sold, mortgaged,
gifted, inherited and bequeathed. With a surge in land registry there has
been an increased reporting of frauds in land registry.And in Kerala, a
high number of fraudulent activities are being reported every year. This
Land fraud detection system identifies land fraud activities. Using fraud
indicators and patterns, it was possible to use Big Data techniques to detect
the fraudulent activities. Digitalized cadastral maps are made available to
public using image processing technology.

14
Bibliography

[1] FRAUD DETECTION AND PREVENTION BY USING BIG DATA

ANALYTICS.” Bineet Kumar Jha, Sivasankari G and Venugopal K
R,Department of Information Science and Engineering, CMR Institute
of Technology Bangalore, IEEE 2020.

[2] ONLINE LAND FRAUD DETECTION AND SAFETY THE PRI-

VACY.” Thamaraiselvi R , Mehanthivinothini G K , Sowntharya K ,
Shreedhivya NInternational Journal of Advanced Research in Biology
Engineering Science and Technology (IJARBEST), March 2016.

[3] ONLINE CREDIT CARD FRAUD DETECTION: A HYBRID

FRAMEWORK WITH BIG DATA TECHNOLOGIES.” You Dai,Jin
Yan,Xiaoxin Tang,Han Zhao and Minyi Guo - IEEE 2016.

[4] BIG DATA ANALYTICS FOR DETECTION OF FRAUDS IN MAT-

RIMONIAL WEBSITES.”Vemula Geeta, P. SivaJyothi, Prof.T.Venkat
Narayana Rao— International Journal of Computer Science Engineering
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Unused “captionsetup[1] on input line

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