BIOMETRICS

Seminar Report Submitted in Partial Fulfillment of the

Requirement for the award of the degree of
BACHELOR OF TECHNOLOGY
IN
ELECTRONICS & INSTRUMENTATION ENGINEERING
( U. P. Technical University , Lucknow )

DEPARTMENT OF ELECTRONICS & INSTRUMENTATION

ENGINEERING

IIMT COLLEGE OF ENGINEERING

GREATER NOIDA

Submitted to Submitted By
Mr.UMESK KUMAR RAHUL KUMAR
Seminar Guide & Coordinator) E.I. Final Year
Roll No. 0721632039
 ACKNOWLEDGEMENT

First and foremost I would like to thank the almighty, who bestowed upon me the
patience, strength and ability to embark upon this work and carry it to its completion. It is
a matter of great pride and privilege for me to have the esteemed supervision of Ms.
Taslima Ahmed as the seminar coordinator.
I would render this acknowledgement as incomplete if I don’t mention the able guidance
of Mr. Umesh Kumar (seminar guide &HOD).I would always be thankful to him for the
critical analysis of my seminar. I am indebt to him for his suggestions that made me
thinking.
I am also thankful to him for providing the internet facility in college premises which
served as a boon in material collection .A special thanks to all the faculty members and
the non teaching staff for their invaluable support.

Rahul Kumar
E.I-Final Year
IIMT College Of Engineering
 CERTIFICATE

THIS IS TO CERTIFY THAT Mr. RAHUL KUMAR OF B.TECH FINAL YEAR,

ELECTRONICS & INSTRUMENTATION DELIVERED A SEMINAR ON
“BIOMETRICS” ON 16 /10 /2009 ACCORDING TO THE U.P. TECHNICAL
UNIVERSITY CURRICULUM. HIS PERFORMANCE IN THE SEMINAR WAS
EXCELLENT/VERY GOOD/SATISFACTORY.

Ms.Taslima Ahmed Mr. Umesh kumar

(Seminar coordinator (HOD&Seminar Guide)
 CONTENTS
DESCRIPTION PAGE NO.

ABSTRACT 1

1) INTRODUCTION 2

2) HISTORY BEHIND BIOMETRIC SECURITY 3-4

3) FINGERPRINTS 4

4) FACE RECOGNITION 5

5) SPEAKER VERIFICATION 6

6) IRIS SCAN 7

7) DYNAMIC SIGNATURE VERIFICATION 8

8) HAND GEOMETRY 8

9) RETINAL SCANNING 8

10) KEYSTROKE DYNAMICS 9

11) IMPLEMENTATION 9-10

12) EVALUATION 10-11

13) CONCLUSION AND FUTURE WORK 12

14) APPLICATION 12-13

15) SUMMARY 14

16) BIBLIOGRAPHY AND REFRENCES 15

 BIOMETRICS – A Future Identity solution

 ABSTRACT
Biometrics is seen by many as a solution to a lot of the user identification and
security problems in today’s networks. Password abuse and misuse, intentional and
inadvertent is a gaping hole in network security. This results mainly from human
error, carelessness and in some cases maliciousness. Biometrics removes human
error from the security equation.

Our paper will examine all the technological and feasibility aspects. We will look
at many different biometric methods of identifying the user.

 This paper describes:

 What is biometrics
 Why would Biometrics be used for computer network security?
 How will Biometric security measures be implemented?
 Where are we now technologically, with regards to feasibility?
 What is the future of Biometrics in networks?
 The pros and cons of Biometric authentication and the likelihood of widespread
public adoption

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 INTRODUCTION

 Biometrics - it’s a word you will hear more and more in the future. It is the technology
that is available today to identify a person by a fingerprint, eye scan, face or handprint, or
voice pattern. The increased emphasis on security in the wake of terrorist attacks, identity
thefts, and computer hackers should be fueling huge growth in the sales of biometric
technology.

Measurements of certain physical or behavioral characteristics of an individual used to

create a unique identifier which can be electronically stored, retrieved, and compared for
positive identification purposes.
Privacy of personal data is an illusion in today’s complex society. With only passwords, or
Social Security Numbers as identity or security measures every one is vulnerable to
invasion of privacy or break of security. Traditional means of identification are easily
compromise and anyone can use this information to assume another’s identity. Sensitive
personal and corporate information can be assessed and even criminal activities can be
performed using another name.

Examples of biometrics:

 Fingerprints
 Hand Geometry
 Voice Recognition
 Iris Scan
 Facial Recognition
 Key stroke dynamic
 Vein patterning
 Signature
 Palm Print
 DNA

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 HISTORY BEHIND BIOMETRIC SECURITY

In fact, the basic principles of biometric verification were understood and practiced
somewhat earlier. Thousands of years earlier to be precise, as our friends in the Nile
valley routinely employed biometric verification in a number of everyday business
situations. There are many references to individuals being formally identified via unique
physiological parameters such as scars, measured physical criteria or a combination of
features such as complexion, eye colour, height and so on. It is well known that some
personnel traits are distinct to each individual and so people can be identified on the basis
of their physical characteristics. Of course, they didn’t have automated electronic
biometric readers and computer networks (as far as we know), and they certainly were
not dealing with the numbers of individuals that we have to accommodate today, but the
basic principles were similar.
Alphonse Bertillon, Chief of the criminal identification division, police department in
France, Paris developed a detail method of identification based on the number of bodily
measurements and physical descriptions. The Bertillon method of anthropometric
identification gained wide acceptance before finger print identification superseded it
.However such recognition is not limited to faces. For example friends or relatives talking
on telephone recognizes one another’s voices.
The most popular Biometrics Characteristics is the finger print. Scientists know form the
number of archeological artifacts that ancient civilization such as those of Babylon and
Later, in the nineteenth century there was a peak of interest as researchers into
criminology attempted to relate physical features and characteristics with criminal
tendencies. This resulted in a variety of measuring devices being produced and much data
being collected.
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The results were not conclusive but the idea of measuring individual physical
characteristics seemed to stick and the parallel development of fingerprinting became the
international methodology among police forces for identity verification.

In parallel, other biometric methodologies such as fingerprint verification were being

steadily improved and refined to the point where they would become reliable, easily
deployed devices. In recent years, we have also seen much interest in iris scanning and
facial recognition techniques which offer the potential of a non contact technology,
although there are additional issues involved in this respect.

 FINGERPRINTS

The patterns of friction ridges and valleys on an individual's fingertips are unique to that
individual. For decades, law enforcement has been classifying and determining identity
by matching key points of ridge endings and bifurcations. Fingerprints are unique for
each finger of a person including identical twins. One of the most commercially available
biometric technologies, fingerprint recognition devices for desktop and laptop access are
now widely available from many different vendors at a low cost. With these devices,
users no longer need to type passwords – instead, only a touch provides instant access.
Fingerprint systems can also be used in identification mode.

 Measures characteristics associated with the friction ridge pattern on the

fingertip
 One of the oldest and most used technology.
 Capture techniques
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– Ink & paper, “inkless” - with subsequent scan
– Electronic: single digit flat scan or swipe across, “10-printers” (rolled)
 Sensor types
– Optical
– Silicon chip
 Capacitive, thermal, e-field

 Fingerprint matching

 Two general algorithm categories

– Minutiae based
 Maps the points where individual ridges start/stop or bifurcate
(branch)
– Image/pattern based
 Aligns and “overlays” images to determine similarity
 Other measurements
– Pattern type
– Ridge counts
– Distance between ridges
– Pores

 FACE RECOGNITION
Biometric face recognition works by using a computer to analyze a subject's facial
structure. Face recognition software takes a number of points and measurements,
including the distances between key characteristics such as eyes, nose and mouth, angles
of key features such as the jaw and forehead, and lengths of various portions of the face.
Using all of this information, the program creates a unique template incorporating all of
the numerical data. This template may then be compared to enormous databases of facial
images to identify the subject.

..........
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 SPEAKER VERIFICATION

Speaker recognition has a history dating back some four decades, where the outputs of
several analog filters were averaged over time for matching. Speaker recognition uses the
acoustic features of speech that have been found to differ between individuals. These
acoustic patterns reflect both anatomy (e.g., size and shape of the throat and mouth) and
learned behavioral patterns (e.g., voice pitch, speaking style). This incorporation of
learned patterns into the voice templates (the latter called "voiceprints") has earned
speaker recognition its classification as a "behavioral biometric." Speaker recognition
systems employ three styles of spoken input: text-dependent, text-prompted and text
independent. Most speaker verification applications use text-dependent input, which
involves selection and enrollment of one or more voice passwords.

Ambient noise levels can impede both collections of the initial and subsequent voice
samples. Performance degradation can result from changes in behavioral attributes of the
voice and from enrollment using one telephone and verification on another telephone.
Voice changes due to aging also need to be addressed by recognition systems. Many
companies market speaker recognition engines, often as part of large voice processing,
control and switching systems. Capture of the biometric is seen as non-invasive. The
technology needs little additional hardware by using existing microphones and voice-
transmission technology allowing recognition over long distances via ordinary telephones
(wire line or wireless)
.Compares live speech with previously created speech model of person’s voice

 Measures multiple characteristics to create voice print, such as frequency,

amplitude, harmonics/sub harmonics, rhythm
 Differences due to vocal tract differences: length, shape of mouth, nasal
cavities, etc.
 Some algorithms use a “cohort list” which groups speakers with similar
characteristics
 Text dependent or independent
 Not speech recognition
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 IRIS SCAN

This recognition method uses the iris of the eye which is the colored area that surrounds
the pupil. Iris patterns are thought unique. The iris patterns are obtained through a video-
based image acquisition system. Iris scanning devices have been used in personal
authentication applications for several years. Systems based on iris recognition have
substantially decreased in price and this trend is expected to continue. The technology
works well in both verification and identification modes (in systems performing one-to-
many searches in a database). Current systems can be used even in the presence of
eyeglasses and contact lenses. The technology is not intrusive. It does not require physical
contact with a scanner. Iris recognition has been demonstrated to work with individuals
from different ethnic groups and nationalities.

Eye pattern recognition system provides a barrier to and virtually eliminates fraudulent
authentication and identity privacy and safety controls privileged access or authorized
entry to sensitive sites, data or material. In addition to privacy protection there are myriad
of applications were iris recognition technology can provide protection and security. This
technology offers the potential to unlock major business opportunities by providing high
confidence customer validation.

Unlike other measurable human features in the face, hand, voice or finger print, the
patterns in the iris do not change overtime and research show the matching accuracy of iris
recognition systems is greater than that of DNA testing. Positive identifications can be
made through glasses, contact lenses and most sunglasses. Automated recognition of
people by the pattern of their eyes offers major advantages over conventional identification
techniques. Iris recognition system also require very little co-operation from the subject,
operate at a comfortable distance and are virtually impossible to deceive. Iris recognition
combines research in computer vision, pattern recognition and the man-machine interface.
The purpose is real-time, high confidence recognition of a person’s identity by
mathematical analysis of the random patterns that are visible with in the iris. Since the iris
is a protected internal organ whose random texture is stable throughout life, it can serve as
a ‘living password’ that one need not remember but one always carries.

 Measures features associated with the random texture of the colored part of
the eye to generate an “Iris code”
 Each eye averages 266 unique features
 Claims no reported false accepts
 Patent held by Iridium, with many licensees
 Sample devices:
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 DYNAMIC SIGNATURE VERIFICATION

 Measures characteristics of handwritten signatures

– Shape, speed, pressure, pen angle, sequence, etc.
 Devices:
– Signature or graphics tablets
– Special pens
 Some algorithms can perform “on-the-fly” verification
 Model adaptation possible

 HAND GEOMETRY

 Measures dimensions of hand, including shape and length of fingers, in 3-D

 Used extensively for physical access control Algorithms
– Full hand and 2-finger
 Devices - hand reader
– Typically lay hand flat
– Pegs guide placement
– Camera positioned above and to side

 RETINAL SCANNING

 Based on the blood vessel patterns at the back of the eye

 Captured by an individual looking through a reticule where a low-intensity light source is
shone through the pupil to illuminate the retina
 Involves 360o circular scan, taking ~400 readings
 Generally used for high-end security applications, primarily for physical access control
 First commercial system available in 1984
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 KEYSTROKE DYNAMICS

 Also known as “typing rhythm” or “typing pattern”

 Analyzes the way a person interacts with a computer keyboard
 Measures variables such as key depression time (duration), latency between
keystrokes, inter key stroke times, typing error frequency, force keystrokes, etc.
 Generally deployed with passwords/pass-phrases
 Purely behavioral biometric

 IMPLEMENTATION

 How does biometrics work?

Biometric authentication requires comparing a registered or enrolled biometric
sample (biometric template or identifier) against a newly captured biometric
sample (for example, a fingerprint captured during a login). During Enrollment a
sample of the biometric trait is captured, processed by a computer, and stored for
later comparison.
Biometric recognition can be used in Identification mode, where the biometric
system identifies a person from the entire enrolled population by searching a
database for a match based solely on the biometric. For example, an entire database
can be searched to verify a person has not applied for entitlement benefits under
two different names. This is sometimes called “one-to-many” matching. A system
can also be used in Verification mode, where the biometric system authenticates a
person’s claimed identity from their previously enrolled pattern. This is also called
“one-to-one” matching. In most computer access or network access environments,
verification mode would be used. A user enters an account, user name, or inserts a
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 EVALUATION

Testing times for technology

Recently, the government agency released findings that show a combination of fingerprint
and facial technologies would be the best option to secure U.S. borders. NIST measured
fingerprint performance using an Immigration and Naturalization Service (INS) database
of 1.2 million prints of 620,000 individuals. Meanwhile the face recognition vendor tests
(FRVT) 2002 measured facial recognition abilities of 10 vendors using the Department of
State's database of 121,000 images of 37,000 individuals.

NIST's Wilson says that to reach the security goals put forth by Congress, the government
will need to launch the combination biometric system to ensure that of the some five
million people that cross the U.S. border, only those with legal permission to enter do so.
Blending biometric capabilities will simply bolster security, especially given the fact that
no system is 100 percent.

In addition to government agencies' tests or deployments of biometrics providing more

credibility to this previously viewed science fiction technology, experts contend that the
establishment of the Bio API standard helps, too.

The Bio API Consortium created the open industry standard to enable software
applications to communicate with a wide variety of biometric technologies.
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Percentage Of Uses Of Different Techniques

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 CONCLUSION AND FUTURE WORK

 Where are biometrics used?

 Healthcare
 Financial
– Check Cashing
– ATMs
 Enterprise Security
– Network authentication
– Single Sign-on
 Casinos
 Banking
 Government
– Border Crossing
– Prison visitor control
– Welfare programs
 Time & Attendance
 Physical Security

 APPLICATION

 Embedded applications
– Automobiles : doors, ignition
– Handguns
– Cell phones
 Computer manufacturers
 Integrated smart cards

Why do we need biometrics?

 Identification
 Authentication
 Trusted Sources
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 Access Privileges

Biometrics can be used to identify you as you. Tokens, such as smart cards,
magnetic stripe cards, photo ID cards, physical keys and so forth, can be lost,
stolen, duplicated, or left at home. Passwords can be forgotten, shared, or
observed. Moreover, today's fast-paced electronic world means people are asked to
remember a multitude of passwords and personal identification numbers (PINs) for
computer accounts, bank ATMs, e-mail accounts, wireless phones, web sites and
so forth. Biometrics holds the promise of fast, easy-to-use, accurate, reliable, and
less expensive authentication for a variety of applications.
There is no one “perfect” biometric that fits all needs. All biometric systems have
their own advantages and disadvantages. There are, however, some common
characteristics needed to make a biometric system usable. First, the biometric must
be based upon a distinguishable trait. For example, for nearly a century, law
enforcement has used fingerprints to identify people. There is a great deal of
scientific data supporting the idea that “no two fingerprints are alike.”
Technologies such as hand geometry have been used for many years and
technologies such as face or iris recognition have come into widespread use. Some
newer biometric methods may be just as accurate, but may require more research
to establish their uniqueness.
Another key aspect is how “user-friendly” a system is. The process should be quick
and easy, such as having a picture taken by a video camera, speaking into a
microphone, or touching a fingerprint scanner. Low cost is important, but most
implementers understand that it is not only the initial cost of the sensor or the
matching software that is involved. Often, the life-cycle support cost of providing
system administration and an enrollment operator can overtake the initial cost of
the biometric hardware.
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 SUMMARY :
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BIBLIOGRAPHY AND REFRENCES:

 Hand and finger print recognition by David Maltoni.

  Bio metric system: technology, design & performance evolution by-James
Wayman
 Biometric: identity assurance in the information age :John D
 Biometric : identity verification in a network world by :Sameer Namavati.
 Internet

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