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ABSTRACT
With the increasing use of electronics and electronic commerce in our day-to-day lives, the importance of fraud-proof identification and recognition systems for use in security applications has grown .The improved understanding of biological systems and the ability to model them using computer algorithms has led to utilization of biometrics in authentication systems. Voice, Iris, Face, Signature, Hand Geometry are the biometrics that have been studied and applied to various kinds of identification and authentication systems.
Biometrics is a means of using parts of the human body as a kind of permanent password. Technology has advanced to the point where computer systems can record and recognize the patterns, hand shapes, ear lobe contours, and a host of other physical characteristics. Using this biometrics, laptop and other portable devices can be empowered with the ability to instantly verify your identity and deny access to everybody else.
CHAPTER 1
BIOMETRICS - AN INTRODUCTION
1.1 INTRODUCTION
Biometrics is a rapidly evolving technology that facilitates the automatic identification of an individual based on his or her physiological or behavioral characteristics.
These characteristics are referred to as biometric identifiers and are unique to each and every one of us. Physiological or physical identifiers do not change overtime and include a personâ„¢s fingerprint, facial features, iris, and retina patterns, along with geometric shape of your hand. Behavioral identifiers do change over time or with mood and include a persons voice, signature and the way one types at keyboard.
As networking grows, so does the number of electronic transactions used for both conducting business and gathering information. This fact has led to realization that the traditional methods involving passwords and pin numbers used to gain entry in these networks, no longer provides adequate security against unauthorized access to sensitive and / or personal data.
Users PIN and passwords can be forgotten and token-based ids such as smart cards, employee badges, passports and drivers license can be lost, stolen or forged. Biometric identification systems provide a solution to these problems, since they require the user to be physically present at the point of identification and unique biometric identifiers are based on who you are, as opposed to what you know or have in your possession.
1.2 DEFINITIONS OF BIOMETRIC
1. Biometrics refers to the method of automatically identifying or verifying identity based upon behavioral or physical traits. It is the science and technology of measuring and statistically analyzing biological data, data that is represented in humans by patterns unique to every individual. [1]
2. Biometrics identification technologies that measure the human body. Biometrics include finger scan (finger print), Iris scan, retina scan, voice verification, hand geometry and signature verification. [2]
3. Biometrics identification devices rely on unique physical characteristics, such as fingerprints, hand shape, or facial appearance to screen and verified individualâ„¢s authority for access and other kind of transactions. [3]
4. Biometrics is a science of measuring the unique physical characteristics of a person such as voice, a face or a fingerprint. These personal features are analyzed and stored as bioprints in a reference database, on a smart card or an embedded chip. They are used to verify the identity of the person by comparing them to the previously stored bioprints. [4]
1.3 WHAT IS A BIOMETRIC? [6]
The security field uses three different types of authentication:
-Something you knowâ€a password, PIN, or piece of information
-Something you haveâ€a card key, smart card, or token
-Something you areâ€a biometric.
Of these, a biometric is the most secure and convenient authentication tool. It can't be borrowed, stolen, or forgotten, and forging one is practically impossible.
Biometrics measure individuals' unique physical or behavioral characteristics to recognize or authenticate their identity. Common physical biometrics include fingerprints; hand or palm geometry; and retina, iris, or facial characteristics. Behavioral characters include signature, voice, keystroke pattern, and gait. Of this class of biometrics, technologies for signature and voice are the most developed.
Figure 1 : Process involved in using a biometric system for security
Capture the chosen biometric; Process the biometric and enroll the biometric template; Store the template; Live-scan the chosen biometric; Process the biometric and extract the biometric template; Match the scanned biometric against stored templates; Provide a matching score to business applications; Record a secure audit trail with respect to system use.
CHAPTER 2
BIOMETRIC TECHNOLOGY
2.1 THE BIOMETRIC MODEL [1]
DATA COLLECTION SIGNAL DECISION
PROCESSING
BIOMETRICS DECISION
PATTERN
MATCHING
PRESENTATION
DATA STORAGE
QUALITY
SENSOR CONTROL DATABASE
FEATURE
EXTRACTION SMARTCARD
TRANSMISSION
IMAGE STORAGE
COMPRESSION
TRANSMISSION
EXPANSION
Figure 2 : The biometric model
A generic biometric model consists of five subsystems, namely data collection, transmission, signal processing, decision-making, and data storage.
Data collection involves use of sensors to detect and measure individualâ„¢s physiological or behavioral characteristics. The measured biometric must be unique and repeatable over multiple measurements. However, technical parameters of sensors, as well as ergonomics of device and the manner in which the biometric characteristics is presented to effect the measurement,
could eventually impact the outcome of the system. For instance, background noise and acoustic of the environment may impact a speech recognition system, while the pressure applied to the finger print scanner might also affect the data.
Not all biometric systems process and store data on the measuring device. Often measurement is made using a relatively simple device to computer or server for processing and/or storage. Depending on the system, data may be relatively large and thus would need to be compressed for quick transfer. The compression algorithm needs to be selected carefully; otherwise it could introduce some artifacts that could impact the decision process.
The signal processing subunit uses feature extraction algorithms to extract true biometric information from the sample in the presence of noise introduced in the data collection and transmission. Additional measurements are made if any flaw or corruption is noted, to ensure good quality.
Pattern matching involves comparing the feature sample to a stored sample. (Biometric data is stored locally on a biometric device, some central database/ server, or on a smart card issued to users) The result of comparison is sent to the decision system to determine the match.
The decision subsystem uses the statistical methods to confirm the authentication if variance between the sample and template is within a certain threshold.
CHAPTER 3
BIOMETRIC TYPES
1. Fingerprint Verification [1,4]
There are variety of approaches to fingerprint verification. Some of them try to emulate the traditional police method of matching minutiae, others are straight pattern matching devices, and some adopt a unique approach all of their own, including moiré Fringe patterns and ultrasonic. Some of them can detect when a live finger is presented, some cannot.There is a greater variety of fingerprint devices available than any other biometric at present.
Figure 3 : Verification by finger scanning and its comparison with database
Potentially capable of good accuracy , fingerprint devices can also suffer from usage errors among insufficiently disciplined users such as might be the case with large user bases. One must also consider the transducer user interface and how this would be affected by large scale usage in a variety of environments. Fingerprint verification may be a good choice for in house systems where adequate explanation and training can be provided to users and where the system is operated within a controlled environment. It is not surprising that the workstation access application area seems to be based almost exclusively around fingerprints, due to the relatively low cost, small size (easily integrated into keyboards) and ease of integration.
2. Voice Verification [5]
Voice authentication is not based on voice recognition but on voice-to-print authentication, where complex technology transforms voice into text. Voice biometrics has the most potential for growth, because it requires no new hardwareâ€most PCs already contain a microphone. However, poor quality and ambient noise can affect verification. In addition, the enrollment procedure has often been more complicated than with other biometrics, leading to the perception that voice verification is not user friendly. Therefore, voice authentication software needs improvement. One day, voice may become an additive technology to finger-scan technology. Because many people see finger scanning as a higher authentication form, voice biometrics will most likely be relegated to replacing or enhancing PINs, passwords, or account names.
3. Retinal Scanning [7]
An established technology where the unique patterns of the retina are scanned by a low intensity light source via an optical coupler. Retinal scanning has proved to be quite accurate in use but does require the user to look into a receptacle and focus on a live of the eye related biometrics. It utilises a fairly conventional ccd camera element and requires no intimate contact between user and reader. In addition it has the potential for higher than average template matching performance. It has been demonstrated to work with spectacles in place and with a variety of ethnic groups and is one of the few devices, which can work well in identification mode. Ease of use and system integration have not traditionally been strong points with the iris scanning devices, but we can expect to see improvements in these areas as new products are introduced. 4. Signature Verification [5]
Signature verification analyzes the way a user signs his/her name. Signing features such as speed, velocity, and pressure are as important as the finished signature's static shape. Signature verification enjoys a synergy with existing processes that other biometrics do not. People are used to signatures as a means of transaction-related identity verification, and most would see nothing unusual in extending this to encompass biometrics. Signature verification devices are reasonably accurate in operation and obviously lend themselves to applications where a signature is an accepted identifier. Surprisingly, relatively few significant signature applications have emerged compared with other biometric methodologies. But if your application fits, it is a technology worth considering.
5. Facial Recognition [4]
Face recognition analyzes facial characteristics. It requires a digital camera to develop a facial image of the user for authentication. This technique has attracted considerable interest, although many people don't completely understand its capabilities. Some vendors have made extravagant claimsâ€which are very difficult, if not impossible, to substantiate in practiceâ€for facial recognition devices. Because facial scanning needs an extra peripheral not customarily included with basic PCs, it is more of a niche market for network authentication. However, the casino industry has capitalized on this technology to create a facial database of scam artists for quick detection by security personnel.
6. Hand Geometry [4]
Hand geometry involves analyzing and measuring the shape of the hand. These biometric offers a good balance of performance characteristics and are relatively easy to use. It might be suitable where there are more users or where users access the system infrequently and are perhaps less disciplined in their approach to the system.
Accuracy can be very high if desired and flexible performance tuning and configuration can accommodate a wide range of applications. Organizations are using hand geometry readers in various scenarios, including time and attendance recording. Ease of integration into other systems and processes, coupled with ease of use, and makes hand geometry an obvious first step for many biometric projects.
7. Software Analysis [3]
Smart protector allows software products to be simply and effectively protective against piracy. Part of application code, completely developed in VB 6.0 is recompiled and transferred at run time executed into a smart card where, due to physical protection, it is in accessible .Smart protector makes it possible also for developers who are not expert of smart card technology to set up, in a very short time, protected and non duplicable software applications.
CHAPTER 4
DETAIL ANALYSIS OF BIOMETRIC
SECURITY SYSTEM USING IRIS SCANNING
4.1 STUCTURE OF AN EYE [7]
An eye is the size of a ping “pong light enters the eye through the pupil, and travels through the lens and the vitreous body to that optic nerve. The optic nerve carries the image of the brain for interpretation. The eye has three chambers known as anterior (front), posterior (back), and the vitreous body. The iris is located at the back end of the anterior chamber.
Figure 4 : Typical structure of an eye
The front chamber contains aqueous humor (a watery fluid). This fluid carries nutrients to different tissues in front of the eye. The cornea is located at the front of this chamber; the cornea is the clear part of the eye. The lens is located at the front of the posterior (back) chamber and is directly behind the iris. This chamber contains a thick gel-like fluid called vitreous humor. This fluid helps to maintain the shape of the eye.
4.2 IRIS SCANNING [7]
An iris based biometric involves analyzing features found in the colored ring of tissue that surrounds the pupil. Iris scanning, uses a fairly conventional camera element and requires no close contact between the user and the reader. In addition, it has the potential for higher than average template -matching performance. Iris biometrics work with glasses in place.
Iris scanning is undoubtedly the less intrusive of the eye related biometrics. It utilizes a fairly conventional CCD camera element and requires no intimate contact between user and reader .It has been demonstrated to work with spectacles in place and with a variety of ethnic groups and is one of the few devices, which can work well in identification mode.
A typical iris scan takes about 30 sec to do and only about two seconds for verification each time thereafter, a camera located about three feet from the subject focuses on and scans the iris from one side and converts this scan into a template i.e. stored for future use.
The final template is based upon unique visible qualities of the iris.
Rings, furrows, freckles-that are characteristics of the individual. Thus when a completed scan is used for identification or verification, actual iris photographs are not compared, but rather digital images of the unique features of these irises.
Robust representations for pattern recognition must be invariant to changes in size, position and orientation of the pattern in the case of iris recognition, this means we must create a representation that is invariant to the optical size of the irises in the image; the size of pupil within the iris; location of the iris within the image; and the iris orientation, which depends upon head tilt, tort ional eye rotation within itâ„¢s socket and camera angles, compounded with imaging through pan / tilt eye finding mirrors that introduces additional image rotation factor as function of eye position , camera position and mirror angles. Fortunately, invariance of all these factors can readily be achieved.
The iris has about 266 unique spots that are used in template construction, versus an average of 13-60 spots employed in another biometric technologies. This is encoded into 512 byte digitized record code known as IRISCODE. It is stored as hexadecimal code in database & can be used in verification at some access point.
Figure 5 : A IRISCODE sample
More over, any differences between a personâ„¢s right and left eyes are statically insignificant so it does not even matter which one is photographed.
The error rate with iris scanning is 1 in 1.2 million and the odds of two irises having the same codes is 1 in 10^52. This said, iris scanning is so accurate that
the entire planet could be enrolled in an iris database and there would still be only marginal chance of a false identification. Even if a person is blinking at the scan and 2/3 of the iris is blocked, the error rate is still an impressive 1 in 100,000 (or the scan can be redone in under a minute).
4.3 HOW THINGS WORK IN IRIS SCANNING [3]
Whilst individual biometric devices ans systems have their own operating methodology, there are some generalizations one can make as to what typically happens within a biometric systems implementation.
[A] TEMPLATE
Before we can verify an individualâ„¢s identity by a biometric we must first capture a sample of the chosen biometric . This sample is referred to as biometric template against which subsequent sample provided at verification time are compared. The template is then reference against an identifier in order to recall it ready for comparison with a live sample at the transaction point. The enrolment procedure and quality of the resultant template are critical factor in the overall success of a biometric application. The size of biometric template itself has some impact on this, with popular methodologies between 9 bytes and 1.5K.
[B] STORAGE
The possible options are as follows :
1) Within the biometric reader device
2) Remotely in a central repository
3) On a portable token such as chip card
[C] VERIFICATION
The verification process requires the user to claim an identity by either entering a PIN or presenting a token, and then verify this claim by providing the live biometric to be compared against the claimed reference template. There will be a resulting match or no match accordingly.
4.4 APPLICATIONS [3]
1. Algorithms developed by John Daugman at Cambridge are today the basis for all iris recognition systems worldwide.
2. In America and Japan, the main applications have been entry control, ATMs, and government programs.
3. In Britain, The National wide Building Society introduced iris recognition within its cash dispensing machines (in lieu of PIN numbers) in1998.
4. Many airports worldwide have recently installed these algorithms for passenger screening and immigration control, including Heathrow, Schiphol, Frankfurt, and Charlotte airports.
Figure 6 : Iris scanning enabled ATM
Figure 7 : An AUTHENTICAM Used for iris scanning
4.5 ADVANTAGES [4]
1.Iris patterns possess a high degree of randomness
2.Variability, entropy, uniqueness
3.Patterns apparently stable throughout life
4.Encoding and decision-making are tractable
5.Image analysis and encoding time: 1 second
6.Decidability index (d -prime): dâ„¢=7.3to 11.4
7.Search period: 100,000 iris codes per second
4.6 DISADVANTAGES [4]
1. Small target (1cm) to acquire from a distance (1m)
2. Moving target ¦within another¦on yet another
3. Located behind a curved, wet, reflecting surface
4. Obscured by eyelashes, lenses, reflections
5. Partially occluded by eyelids, often drooping
6. Illumination should not be visible or bright
CHAPTER 5
SELECTING BIOMETRIC TECHNOLOGY
Biometric technology is one area that no segment of the IT industry can afford to ignore. Biometrics provides security benefits across the spectrum, from IT vendors to end users, and from security system developers to security system users. Different technologies may be appropriate for different applications, depending on perceived user profiles, the need to interface with other systems or databases, environmental conditions, and a host of other application-specific parameters.
Table 1: Comparison of biometrics [2]
Characteristic Fingerprints Hand
Geometry Retina Iris Face Signature Voice
Ease of Use High High Low Medium Medium High High
Error incidence Dryness, dirt, age Hand injury, age Glasses Poor Lighting Lighting, age, glasses, hair Changing signatures Noise, colds, weather
Accuracy High High Very High Very High High High High
Cost * * * * * * *
User acceptance Medium Medium Medium Medium Medium Medium High
Required security level High Medium High Very High Medium Medium Medium
Long-term stability High Medium High High Medium Medium Medium
*The large number of factors involved makes a simple cost comparison impractical.
5.1 EASE OF USE
Some biometric devices are not user friendly. For example, users without proper training may experience difficulty aligning their head with a device for enrolling and matching facial templates.
5.2 ACCURACY [2,5]
Vendors often use two different methods to rate biometric accuracy: false-acceptance rate or false-rejection rate. Both methods focus on the system's ability to allow limited entry to authorized users. However, these measures can vary significantly, depending on how you adjust the sensitivity of the mechanism that matches the biometric. For example, you can require a tighter match between the measurements of hand geometry and the user's template. This will probably decrease the false-acceptance rate, but at the same time can increase the false-rejection rate. So be careful to understand how vendors arrive at quoted values of FAR and FRR.
False accept rates (FAR) indicate the likelihood that an impostor may be falsely accepted by the system.
False reject rates (FRR) indicate the likelihood that the genuine user may be rejected by the system.
Because FAR and FRR are interdependent, it is more meaningful to plot them against each other, as shown in figure. Each point on the plot represents a hypothetical system's performance at various sensitivity settings. With such a
plot, you can compare these rates to determine the crossover error rate. The lower the CER, the more accurate the system.
Figure 9 : Crossover error rate attempts to combine two measures of biometric accuracy
Generally, physical biometrics is more accurate than behavioral biometrics.
5.3 COST
Cost components include :-
Biometric capture hardware
Back-end processing power to maintain the database
Research and testing of the biometric system
Installation, including implementation team salaries
Mounting, installation, connection, and user system integration costs
User education, often conducted through marketing campaigns
CHAPTER 6
BIOMETRICS APPLICATIONS
6.1 INDIAN INITIATIVES [1]
Bioenable Technology, Pune, is a software company that develops biometric products to cater to tough Indian working conditions and environments. The firm has developed intelligent biometric solutions for physical access control, banking transaction, timing, and attendance applications.
Siemens Information System Limited (SISL), Banglore, has developed a text-independent autonomous speech recognition system to identify and authorise a speaker by analyzing his voice. Central forensic laboratories, Chandigarh, uses this system to track down and identify criminals by comparing their voice samples using SISL software. Other innovations of SISL include fingerprint identification and management system (FIMs), language-independent speech recognition system, and optical character recognition system.
Axis Software, Pune, deals in fingerprint, iris and face recognition technology and is planning to add voice recognition technology to its range of voice authentication products and systems. The axis system stores biometric records in an encrypted template in digital form. The record by itself is of no use to a stealer and cannot be reconstructed to reveal a persons identity to someone else.
Jaypeetex, Mumbai, has introduced biometric technologies for security, access control, timing, and attendance applications.
Biometric society of India (INBIOS), affiliated to international society of computational biology (ISCB), provides innovative professional solutions and services dedicated to bioinformatics.
6.2 GLOBAL DEVELOPMENTS [1]
Internet security: Litronix, USA, a leading provider of public key infrastructure (PKI) based internet security solutions, has developed biometric identification techniques for use in electronic data applications such as digital network and smart cards. The smart card, integrating voice and handwritten functions, incorporates the appropriate biometric template to deliver the final match and authorization. The company plans to incorporate capture, manipulation, enrollment and extraction features in smart card reader also.
Windows Biometrics: Microsoft has announced plans to integrate biometric authentication technology in future versions of its windows operating systems. For this it has acquired I/O software Inc.s biometric API technology (BAPI) and secures suites core authentication technology. The software will enable windows users to log on and conduct secure e-commerce transactions using a combination of fingerprint, iris pattern, and voice recognition instead of password.
Net Nanny Software International has developed biometric software to provide extra security to Windows NT networks. The biopassword log on feature for Windows NT will back client/server biometrics application to recognize a users typing pattern and use it to authenticate the user to the network. The software uses a mathematical algorithm to record pressure, speed, and rhythm as a user name and password.
Biometric smart cards: Polaroid and Atmel have developed secure identity cards that merge ultra-secure smart cards, fingerprint verification, biometric identification, and digital imaging. These cards will be used in ecommerce, online, remote access, and any it environment where authentication is required.
Biometrics cellular: fujistu microelectronics has developed an innovative fingerprint identification system that combines sweep sensor technology with advanced algorithms to provide a powerful, dependable, easy to use authentication for vices. A single fingerprint sweep across the sensor captures features to rapidly authenticate users of cell phones and PDAs.
CHAPTER 7
THE FUTURE OF BIOMETRICS
There are many views concerning potential biometric applications, some popular examples being: [1,5] ATM machine use :
Most of the leading banks have been experimenting with biometrics for ATM machine use and as a general means of combating card fraud. Surprisingly, these experiments have rarely consisted of carefully integrated devices into a common process, as could easily be achieved with certain biometric devices. Previous comments in this paper concerning user psychology come to mind here and one wonders why wehave not seen a more professional and carefully considered implementation from this sector. The banks will of course have a view concerning the level of fraud and the cost of combating it via a technology solution such as biometrics. They will also express concern about potentially alienating customers with such an approach. However, it still surprises many in the biometric industry that the banks and financial institutions have so far failed to embrace this technology with any enthusiasm. Travel and tourism :
There are many in this industry who have the vision of a multi application card for travelers which, incorporating a biometric, would enable them to participate in various frequent flyer and border control systems as well as paying for their air ticket, hotel room, hire care etc., all with one convenient token.
Technically this is eminently possible, but from a political and commercial point of view there are still many issues to resolve, not the least being who would own the card, be responsible for administration and so on. These may not be insurmountable problems and perhaps we may see something along these lines emerge. A notable challenge in this respect would be packaging such an initiative in a way that would be truly attractive for users. Public identity cards :
A biometric incorporated into a multi purpose public ID card would be useful in a number of scenarios if one could win public support for such a scheme. Unfortunately, in this country as in others there are huge numbers of individuals who definitely do not want to be identified. This ensures that any such proposal would quickly become a political hot potato and a nightmare for the minister concerned. You may consider this a shame or a good thing, depending on you point of view. From a dispassionate technology perspective it represents something of a lost opportunity, but this is of course nothing new. Itâ„¢s interesting that certain local authorities in the UK have issued Ëœcitizenâ„¢ cards with which named cardholders can receive various benefits including discounts at local stores and on certain services. These do not seem to have been seriously challenged, even though they are in effect an ID card.
CHAPTER 8
CONCLUSION
The security requirements of the future require a much higher level of physical verification and attention to increasingly sophisticated fraud and electronic hacking. Smart ID cards provide this ultra high level of security in the familiar ID card format everyone is used to.
No more the nuisance of forgotten passwords and ID codes, biometric based authentication is here. Your fingerprints, iris pattern, and voice will verify your identity at ATMs, airports, etc. You can unlock your house or withdraw money from your bank with just a blink of eye, a tap of your finger, or by just showing your face.
BIBLIOGRAPHY
[1] Biometrics : Journal of International Biometric Society
[2] The Biometrics Constrium ¦¦¦¦¦..May 2002
[3] Electronics For You ¦¦¦¦¦¦¦¦June 2002
[4] biometric.com
[5] bioventric.com
[6]
http://homepage.ntlworldavanti
[7]
http://ibia.org
TABLE OF CONTENTS
Page No.
ABSTRACT 1
1. BIOMETRICS -AN INTODUCTION 2
1.1 INTRODUCTION 2
1.2 DEFINITIONS OF BIOMETRIC 3
1.3 WHAT IS A BIOMETRIC? 3
2. BIOMETRIC TECHNOLOGY 5
2.1 THE BIOMETRIC MODEL 5
3. BIOMETRIC TYPES 7
4. DETAIL ANALYSIS OF BIOMETRIC SECURITY SYSTEM USING IRIS SCANNING 11
4.1 STRUCTURE OF AN EYE 11
4.2 IRIS SCANNING 12
4.3 HOW THINGS WORK IN IRIS SCANNING 14
4.4 APPLICATIONS 15
4.5 ADVANTAGES 17
4.6 DISADVANTAGES 17
5. SELECTING BIOMETRIC TECHNOLOGY 18
5.1 EASE OF USE 19
5.2 ACCURACY 19
5.3 COST 20
6. BIOMETRICS APPLICATIONS 21
6.1 INDIAN INITIATIVES 21
6.2 GLOBAL DEVELOPMENTS 22
7. THE FUTURE OF BIOMETRICS 24
8. CONCLUSION 26
BIBLIOGRAPHY 27
APPENDIX : POWER POINT SLIDES 28
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