biometric authentication green apple computer learning

Sharbani Bhattacharya

Biometric Authentication

Green Apple Computer Learning

Faridabad

Three Courses

• Biometric Authentication Introduction-free online course

• Biometric Authentication and Security- Basic Course

• Design & Development of Biometric Authentication – Advanced Course

12/8/2016 Green Apple Computer Learning 2

Today’s Topic

Biometric Authentication

Introduction12/8/2016 Green Apple Computer Learning 3

Problems with Current SecuritySystems

• Based on Passwords, or ID/Swipe cards

• Can be Lost.

• Can be forgotten.

• Worse! Can be stolen and used by a thief/intruder to access your data, bank accounts, car etc.


User/Passwords

• With increasing use of IT technology and need to protect data, we have multiple accounts/passwords.

• We can only remember so many passwords, so we end up using things we know to create them (birthdays, wife/girlfriends name, dog, cat…)

• Its is easy to crack passwords, because most of our passwords are weak!

• If we create strong passwords (that should be meaningless to us) we will forget them! And there is no way to remember multiple such passwords


Biometric Authentications

Biometrics are based on the principle of measurable physiological or behavioral characteristics such as a fingerprint or a voice sample or retina or handwriting and so on.


Advantage

The advantage that Biometrics presents is that the information is unique for each individual and that it can identify the individual in spite of variations in the time (it does not matter if the first biometric sample was taken year ago).The pillars of e-learning security are: authentication, privacy (data confidentiality) authorization (access control), data integrity and non-repudiation. Biometric is a technique that can provide all this requirements with quite lot reliability.


Disadvantage

• It can insecure by any chance the database hacked here biometrics are stored.

• Encryption may give different results and may not match sometime.

• Biometrics may be useless when due accident or mishap the user looses part of body or organ which is used for biometric authentication.


Biometrics used in History

China is among the first known to practice biometrics back in the fourteenth century as reported by the Portuguese historian Joao de Barros. It was called member-printing where the children's palms as well as the footprints were stamped on paper with ink to identify each baby.



Alphonse Bertillon, a Paris based anthropologist and police desk clerk was trying to find a way of identifying convicts in the 1890s decided to research on biometrics. He came up with measuring body lengths and was relevant till it was proved to be prone to error as many people shared the same measurement.



The police started using fingerprinting developed based on the Chinese methods used century before by Richard Edward Henry, who was working at the Scotland Yard.



Raina, Orlans and Woodward (2003, p. 25-26) stated references to biometrics as a concept could be traced back to over a thousand years in East Asia where potters placed their fingerprints on their wares as an early form of brand identity. They also pointed Egypt's Nile Valley where traders were formally identified based on physical characteristics such as eye color, complexion and also height. The information were used by merchant to identify trusted traders whom they had successfully transacted business with in the past.


Biometrics used in Bible

Kapil et al also made references to the Bible, first pointing to the faith Gileadites had in their biometric system as reported in The Book of Judges (12:5-6) that the men of Gilead identified enemy in their midst by making suspected Ephraimites say "Shibboleth" for they could not pronounce it right.



The second reference is to The Book of Genesis (27:11-28) where Jacob pretended to be Esau by putting goat skins on his hands and back of his neck so his skin would feel hairy to his blind, aged father's touch. This illustrates a case of biometric spoofing and false acceptance.


Biometric Systems

Biometric systems can be used in two different modes

• Identity verification (also called one-to-one comparison or authentication) occurs when the user1 claims to be already enrolled in the system (presents an ID card or login name); in this case the biometric data obtained from the user are compared to the user's data already stored in the database.

• Identification (also called search, recognition or one-to-many comparison) occurs when identity of the user is a priori unknown.


Biometric Systems

There are basically two kinds of biometric systems-

• Automated identification systems operated by professionals (e.g., police Automated Fingerprint Identification Systems – AFIS).

• Biometric Authentication Systems


Automated Identification Systems

Automated identification systems operated by professionals (e.g., police Automated Fingerprint Identification Systems – AFIS). The purpose of such systems is to identify an individual in question or to find an offender of a crime according to trails left at the crime scene. Enrolled users do not typically have any access to such systems and operators of such systems do not have many reasons to cheat.


Biometric Authentication Systems

Biometric authentication systems used for access control. These systems are used by ordinary users to gain a privilege or an access right. Securing such a system is a much more complicated task.


Biometric

Biometric characteristics can be divided in two main classes-

• Physiological are related

• Behavioral are related


Physiological are related

Physiological are related to the shape of the body and thus it varies from person to person Fingerprints, Face recognition, hand geometry and iris recognition are some examples of this type of Biometric.


Behavioral are related

Behavioral are related to the behavior of a person. Some examples in this case are signature, keystroke dynamics and of voice . Sometimes voice is also considered to be a physiological biometric as it varies from person to person.


Accuracy & Cost of Biometric Systems


Comparison of Biometric Methods


What are Biometrics?

The term "biometrics" is derived from the Greek words bio (life) and metric (to measure).


Future

• A biometric system can provide two functions. One of which is verification and the other one is Authentication.

• So, the techniques used for biometric authentication has to be stringent enough that they can employ both these functionalities simultaneously.


Future

• Currently, cognitive biometrics systems are being developed to use brain response to odor stimuli, facial perception and mental performance for search at ports and high security areas.

• Other biometric strategies are being developed such as those based on gait (way of walking), retina,

• Hand veins, ear canal, facial thermogram , DNA, odor and scent and palm prints. In the near future, these biometric techniques can be the solution for the current threats in world of information security.


Different Biometrics1. Face2. Fingerprint3. Voice4. Palm print5. Hand Geometry6. Hand Vein7. Iris8. Retina Scan9. DNA10. Ear Shape11. Signatures12. Gait13. Keystroke14. Body Odr15. Thermal Imaging


FaceA facial recognition technique is an application of computer for automatically identifying or verifying a person from a digital image or a video frame from a video source. It is the most natural means of biometric identification.Facial recognition technologies have recently developed into two areas and they are Facial metric and Eigen faces.Facial metric technology relies on the manufacture of the specific facial features (the system usually look for the positioning of eyes, nose and mouth and distances between these features).• The face region is rescaled to a fixed pre-defined size (e.g.

150-100 points). • This normalized face image is called the canonical image.

Then the facial metrics are computed and stored in a face template. The typical size of such a template is between 3 and 5 KB.


Strengths of Facial Recognition

• It is capable of leveraging existing image acquisition equipment.

• It is capable of searching against static image such as passports and driver's license photographs.

• It is the only biometric capable of operating without user cooperation.


Weaknesses of Facial Recognition

• Matching accuracy is reduced by change in acquisition environment.

• Matching accuracy is also reduced by changes in physiological characteristics.

• Tendency of privacy abuse is high due to non-cooperative enrollment and identification capabilities.


FingerprintA fingerprint is an impression of the friction ridges of all or any part of the finger. A friction ridge is a raised portion of the on the palmar (palm) or digits (fingers and toes) or plantar (sole) skin, consisting of one or more connected ridge units of friction ridge skin. These ridges are sometimes known as "dermal ridges" or "dermal ". The traditional method uses the ink to get the finger print onto a piece of paper. This piece of paper is then scanned using a traditional scanner. Now in modern approach, live finger print readers are used .These are based on optical, thermal, silicon or ultrasonic principles. It is the oldest of all the biometric techniques. Optical finger print reader is the most common at present. They are based on reflection changes at the spots where finger papilar lines touch the reader surface.All the optical fingerprint readers comprise of the source of light, the light sensor and a special reflection surface that changes the reflection according to the pressure. Some of the readers are fitted out with the processing and memory chips as well.


Fingerprint


Strengths of Deploying Fingerprint Technology

• It can be used in a range of environment.

• It is a mature and proven core technology capable of high level accuracy.

• It employs ergonomic and easy-to-use devices.

• The ability to enroll multiple fingers can increase system accuracy and flexibility.


Weaknesses of Fingerprint Technology

• Most devices are unable to enroll some small percentage of users.

• Performance can deteriorate over time.

• It is associated with forensic applications.


VoiceVoice is also physiological trait because every person has different pitch, but voice recognition is mainly based on the study of the way a person speaks, commonly classified as behavioral.Speaker verification focuses on the vocal characteristics that produce speech and not on the sound or the pronunciation of speech itself. The vocal characteristics depend on the dimensions of the vocal tract, mouth, nasal cavities and the other speech processing mechanism of the human body. It doesn’t require any special and expensive hardware.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).Speaker recognition system employs three styles of spoken input and they are listed below.(a) Text dependent (b) Text prompted (c) Text independentText dependent involves selection and enrollment of one or more voice passwords.Text prompted is used whenever there is concern of imposters.12/8/2016 Green Apple Computer Learning 35

Strengths of Voice-Scan Technology

• It is capable of leveraging telephony infrastructure.

• It effectively layers with other processes such as speech recognition and verbal passwords.

• It generally lacks the negative perceptions associated with other biometrics.


Weaknesses of voice-scan technology

• It is potentially more susceptible to replay attacks than other biometrics.

• Its accuracy is challenged by low-quality capture devices, ambient noise, etc.

• The success of voice-scan as a PC solution requires users to develop new habits.

• The large size of the template limits the number of potential applications.


Palm print

Palm print verification is a slightly different implementation of the fingerprint technology. Palm print scanning uses optical readers that are very similar to those used for fingerprint scanning, their size is, however, much bigger and this is a limiting factor for the use in workstations or mobile devices.


Hand Geometry

It is based on the fact that nearly every person’s hand is shaped differently and that the shape of a person’s hand does not change after certain age.

These techniques include the estimation of length, width, thickness and surface area of the hand. Various method are used to measure the hands- Mechanical or optical principle.


Hand Geometry


Hand Geometry

There are two sub-categories of optical scanners. Devices from first category create a black and white bitmap image of the hand’s shape. This is easily done using a source of light and a black and white camera. The bitmap image is processed by the computer software. Only 2D characteristics of hand can be used in this case. Hand geometry systems from other category are more complicated. They use special guide marking to portion the hand better and have two (both vertical and horizontal) sensors for the hand shape measurements. So, sensors from this category handle data of all 3D features.


Strengths of Hand-Scan Technology

• It is able to operate in challenging environments.

• It is an established, reliable core technology.

• It is generally perceived as non intrusive.

• It is based on relatively stable physiological characteristics.


Weaknesses of Hand-Scan Technology

• It has limited accuracy.

• The form factor limits the scope of potential applications.

• The ergonomic design limits usage by certain populations.


Hand Vein

Hand vein geometry is based on the fact that the vein pattern is distinctive for various individuals. The veins under the skin absorb infrared light and thus have a darker pattern on the image of the hand taken by an infrared camera.

The hand vein geometry is still in the stage of research and development. One such system is manufactured by British Technology Group. The device is called Vein check and uses a template with the size of 50 bytes.


IrisThis recognition method uses the iris of the eye which is colored area that surrounds the pupil. Iris patterns are unique and are obtained through video based image acquisition system.Each iris structure is featuring a complex pattern. This can be a combination of specific characteristics known as corona, crypts, filaments, freckles, pits, furrows, striations and rings.The iris pattern is taken by a special gray scale camera in the distance of 10-40 cm of camera. Once the gray scale image of the eye is obtained then the software tries to locate the iris within the image. If an iris is found then the software creates a net of curves covering the iris. Based on the darkness of the points along the lines the software creates the iris code.

Here, two influences have to take into account. First, the overall darkness of image is influenced by the lighting condition so the darkness threshold used to decide whether a given point is dark or bright cannot be static, it must be dynamically computed according to the overall picture darkness. Secondly, the size of the iris changes as the size of the pupil changes. Before computing the iris code, a proper transformation must be done.


Iris

In decision process, the matching software takes two iris codes and compute the hamming distance based on the number of different bits. The hamming distances score (within the range 0 means the same iris codes), which is then compared with the security threshold to make the final decision. Computing the hamming distance of two iris codes is very fast (it is the fact only counting the number of bits in the exclusive OR of two iris codes). We can also implement the concept of template matching in this technique. In template matching, some statistical calculation is done between a stored iris template and a produced. Depending on the result decision is taken.


Strengths of Iris-Scan Technology

• It has the potential for exceptionally high levels of accuracy.

• It is capable of reliable verification as well as identification.

• It maintains stability of characteristics over a lifetime frame.


Weaknesses of Iris-scan Technology

• It has a propensity for false rejection.

• Acquisition of the images requires moderate attentiveness and training.

• Some users exhibit a certain degree of discomfort with eye-based technology.

• A proprietary acquisition device is required for deployment.


Retina Scan

It is based on the blood vessel pattern in the retina of the eye as the blood vessels at the back of the eye have a unique pattern, from eye to eye and person to person. Retina is not directly visible and so a coherent infrared light source is necessary to illuminate the retina. The infrared energy is absorbed faster by blood vessels in the retina than by the surrounding tissue. The image of the retina blood vessel pattern is then analyzed.


Retina

• Retina scans require that the person removes their glasses, place their eye close to the scanner, stare at a specific point, and remain still, and focus on a specified location for approximately 10 to 15 seconds while the scan is completed.

• A retinal scan involves the use of a low-intensity coherent light source, which is projected onto the retina to illuminate the blood vessels which are then photographed and analyzed.

• A coupler is used to read the blood vessel patterns. A retina scan cannot be faked as it is currently impossible to forge a human retina.

• Furthermore, the retina of a deceased person decays too rapidly to be used to deceive a retinal scan. A retinal scan has an error rate of 1 in 10,000,000, compared to fingerprint identification error being sometimes as high as 1 in 500.


Strength of Retina Scan

• . A retina scan cannot be faked as it is currently impossible to forge a human retina.


Weakness of Retina Scan

• The retina of a deceased person decays too rapidly to be used to deceive a retinal scan.

• Mishap and accidents can be make useless the method.


DNA

DNA sampling is rather intrusive at present and requires a form of tissue, blood or other bodily sample. This method of capture still has to be refined. So far the DNA analysis has not been sufficiently automatic to rank the DNA analysis as a biometric technology. The analysis of human DNA is now possible within 10 minutes.

As soon as the technology advances so that DNA can be matched automatically in real time, it may become more significant. At present Biometric Systems DNA is very entrenched in crime detection and so will remain in the law enforcement area for the time being.


Ear Shape

Identifying individuals by the ear shape is used in law enforcement applications where ear markings are found at crime scenes. Whether this technology will progress to access control applications is yet to be seen. An ear shape verifier (Optophone) is produced by a French company ART Techniques. It is a telephone type handset within which

is a lighting unit and cameras which capture two images of the ear


Signatures

The signature dynamics recognition is based on the dynamics of making the signature, rather than a direct comparison of the signature itself afterwards. The dynamics is measured as a means of the pressure, direction, acceleration and the length of the strokes, dynamics number of strokes and their duration. The most obvious and important advantage of this is that a fraudster cannot glean any information on how to write the signature by simply looking at one that has been previously written. There are various kinds of devices used to capture the signature dynamics. These are either traditional tablets or special purpose devices. Tablets capture 2D coordinates and the pressure.


GaitGait biometrics is a biometrics that is based on the way the person walks. It should be mentioned that gait is not affected by the speed of the person’s walk.

Some scientists differentiate gait from gait recognition, pointing out that gait can be considered as a cyclic combination of movements that results in human locomotion and gait recognition is recognition of some property style of walk, pathology, etc. (Bi-ometric Gait Recognition) .


Gait

• Kinematic parameters such as knee, ankle movements and angles.

• Spatial-temporal parameters as length and width of steps, walking speed.

• Correlation between parameters.


Properties of Gait

According to Bertenthal and Pinto there are 3 important properties of human perception of gait:

1. Frequency entertainment: various components of the gait share a common frequency.

2. Phase locking: the relationships among the components of the gaits remain stable.

3. Physical plausibility.


Strength of GAIT Technology

• Walking style cannot be copied.

• Every individual have peculiar style of walk which good source of identification.


Weakness of GAIT Technology

• It may change due time and age.

• Dresses may cause difference in walking style. Wearing saree , pant and skirt may change accuracy level.

• Minor accident and mishap may change identifying and verification process.


Keystroke

Keystroke dynamics is a method of verifying the identity of an individual by their typing rhythm which can cope with trained typists as well as the amateur two-finger typist.

Systems can verify the user at the log-on stage or they can continually monitor the Biometric Systems 32 typist. These systems should be cheap to install as all that is needed is a software package.


Body Odor

The body odor biometrics is based on the fact that virtually each human smell is unique. The smell is captured by sensors that are capable to obtain the odor from nonintrusive parts of the body such as the back of the hand. Methods of capturing a person’s smell are being explored by Mastiff Electronic Systems. Each human smell is made up of chemicals known as volatiles. They are extracted by the system and converted into a template.The use of body odor sensors brings up the privacy issue as the body odor carries a significant amount of sensitive personal information. It is possible to diagnose some diseases or activities in the last hours (like sex, for example) by analyzing the body odor.


Thermal Imaging

This technology is similar to the hand vein geometry. It also uses an infrared source of light and camera to produce an image of the vein pattern in the face or in the wrist.


Mix and Match of Authentication Techniques

• The six experimental conditions were as follows: • Password: Enter an alphanumeric password using the built-in on-screen

keyboard. In the spirit of typical corporate password policies, the easy to remember 8character password securit3 was used.

• Voice: The user must speak the password phrase“ three five seven nine three five seven nine”.

• Face: The user must take a photograph of their face using the front-facing camera.

• Gesture: The user must write ‘35793579’ on the screen with their finger. • Face+Voice: The user must say “three five seven nine three five seven

nine” while simultaneously lining up their face and taking a photograph. • Gesture+Voice: The user must say “three five seven nine three five seven

nine”while simultaneously writing the digits ‘35793579’ on the screen with their finger.


Biometrics Are not Used Somewhere

• Biometrics offer great amount of benefits in safeguarding systems and is perceived as more reliable than other security techniques (traditional security methods). However, biometric technologies are not the perfect security to be deployed for every application and in some cases biometric authentication is just not the right solution."

• One of the major challenges facing the biometric industry is defining those environments in which biometrics offer the strongest benefits to both individuals and institutions, and then showing that the benefits of deployment outweigh the risk as well as the costs


Security

Since biometric characteristics cannot be guessed or stolen, biometric systems offer a higher degree of security than typical authentication methods (passwords or tokens).Efficient passwords are traditionally characterized by a long and alternated sequence of numbers and symbols. Therefore, they are sometimes difficult to remember.Tokens, on their hand, may be stolen or loosed. Regardless of their authentication type, passwords or tokens can be shared. In this sense, there is no certainty of who is the actual user. Since biometric characteristics are not shared, this shortcoming is almost solved.


Accountibility

One important benefit of using biometric-based authentication systems is that they are able to keep track of the user's activities, e.g. it is possible to know who has been doing what at a given time (when).

These benefits are not available in traditional authentication systems, since users may share their identification cues, being not possible, for example, to know who is the actual user.


Convenience

Biometrics systems are convenient in environments where access privileges are necessary. Traditionally, in many authentication environments, a user may have different tokens or passwords. In these cases, biometrics can be used to simplify the authentication process since the multiple passwords or tokens can be replaced by a single biometric characteristics.Furthermore, another benefit is that biometric systems are easily scalable. Depending on the security level desired, more sophisticated biometric characteristics could be used. At a bottom level, one could use for example, characteristics that are not very discriminative. If more discriminable properties are desired in the system, biometric characteristics with higher distinctive properties may be used.


Application• The operational goals of biometric applications are just as variable as the

technologies: some systems search for known individuals; some search for unknown individuals.

• Some verify a claimed identity; some verify an unclaimed identity; and some verify that the individual has no identity in the system at all.

• Some systems search one or multiple submitted samples against a large database of millions of previously stored “templates” – the biometric data given at the time of enrollment.

• Some systems search one or multiple samples against a database of a few “models” – mathematical representations of the signal generation process created at the time of enrollment.

• Some systems compare submitted samples against models of both the claimed identity and impostor identities. Some systems search one or multiple samples against only one “template” or “model”.


Application

The application environments can vary greatly –outdoors or indoors, supervised or unsupervised, with people trained or not trained in the use of the acquisition device.


Biometric System

A biometric system can be designed to test one of only two possible hypotheses: (1) that the submitted samples are from an individual known to the system; or (2) that the submitted samples are from an individual not known to the system. Applications to test the first hypothesis are called “positive identification” systems (verifying a positive claim of enrollment), while applications testing the latter are “negative identification” systems (verifying a claim of no enrollment)


Application

• “Positive” and “negative” identification are “duals” of each other.

• Positive identification systems generally serve to prevent multiple users of a single identity, while negative identification systems serve to prevent multiple identities of a single user.


Application

Use of biometrics in negative identification systems must be mandatory for all users because no alternative methods exist for verifying a claim of no known identity.


Overt Versus Covert

The first partition is “overt/covert”. If the user is aware that a biometric identifier is being measured, the use is overt. If unaware, the use is covert. Almost all conceivable access control and non-forensic applications are overt. Forensic applications can be covert.


Habituated Versus Non-Habituated

The second partition, “habituated/non-habituated”, applies to the intended users of the application. Users presenting a biometric trait on a daily basis can be considered habituated after a short period of time. Users who have not presented the trait recently can be considered “non-habituated”.A more precise definition will be possible after we have better information relating system performance to frequency of use for a wide population over a wide field of devices. If all the intended users are “habituated”, the application is considered a “habituated” application. If all the intended users are “non-habituated”, the application is considered “non habituated”.


Attended Versus Non-Attended

A third partition is “attended/unattended”, and refers to whether the use of the biometric device during operation will be observed and guided by system management. Non-cooperative applications will generally require supervised operation, while cooperative operation may or may not.

Nearly, all systems supervise the enrollment process, although some do not.


Standard Versus Non-Standard Environment

A fourth partition is “standard/non-standard operating environment”. If the application will take place indoors at standard temperature (20°C),pressure (1 atm), and other environmental conditions, particularly where lighting conditions can be controlled, it is considered a “standard environment” application. Outdoor systems, and perhaps some unusual indoor systems, are considered “non-standard environment” applications.


Public Versus Private

A fifth partition is “public/private”. Will the users of the system be customers of the system management (public) or employees (private)? Clearly, attitudes toward usage of the devices, which will directly affect performance, vary depending upon the relationship between the end-users and system management.


Open Versus ClosedA sixth partition is “open/closed”. Will the system be required, now or in the future, to exchange data with other biometric systems run by other management?

For instance, some US state social services agencies want to be able to exchange biometric information with other states. If a system is to be open, data collection, compression and format standards are required. A closed system can operate perfectly well on completely proprietary formats.


Biometrics and Privacy.1. Unlike more common forms of identification, biometric measures contain no personal information and are more difficult to forge or steal.

2. Biometric measures can be used in place of a name or Social Security number to secure anonymous transactions.

3. Some biometric measures (face images, voice signals and “latent” fingerprints left on surfaces) can be taken without a person’s knowledge, but cannot be linked to an identity without a pre-existing invertible database.

4. A Social Security or credit card number, and sometimes even a legal name, can identify a person in a large population. This capability has not been demonstrated using any single biometric measure.

5. Like telephone and credit card information, biometric databases can be searched outside of their intended purpose by court order.

6. Unlike credit card, telephone or Social Security numbers, biometric characteristics change from one measurement to the next.

7. Searching for personal data based on biometric measures is not as reliable or efficient as using better identifiers, like legal name or Social Security number.

8. Biometric measures are not always secret, but are sometimes publicly observable

and cannot be revoked if compromised.12/8/2016 Green Apple Computer Learning 80

Adhaar Card


Template Security Requirements

The main challenge in developing a biometric template protection scheme is to achieve an acceptable tradeoff among three requirements

• Non-invertibility

• Discriminability

• Revocability


Non-invertibility

It must be computationally hard to recover the biometric features from the stored template. This prevents the adversary from replaying the biometric features gleaned from the template or creating physical spoofs of the biometric trait.


Discriminability

The template protection scheme shouldn’t degrade the biometric system’s authentication accuracy.


Revocability

It should be possible to create multiple secure templates from the same biometric data that aren’t linkable to that data. This property not only enables the biometric system to revoke and reissue new biometric templates if the database is compromised, but it also prevents cross-matching across databases, thereby preserving the user’s privacy.


Template Security Approaches

• Biometric Feature Transformation

• Biometric Cryptosystems


Biometric Feature Transformation

The secure template is derived by applying a noninvertible or one-way transformation function to the original template; this transformation is typically based on user-specific parameters.

During authentication, the system applies the same trans-formation function to the query and matching occurs in the transformed domain.


Biometric Cryptosystems

It store only a fraction of the information derived from the biometric template known as the secure sketch. While the secure sketch in itself is insufficient to reconstruct the original template, it does contain sufficient data to recover the template in the presence of another biometric sample that closely matches the enrollment sample.


Why we need Biometric Standards

Stapleton (2003, p. 167) defined a standard in a general term as "a published document, developed by a recognized authority, which defines a set of policies and practices, technical or security requirements, techniques or mechanisms, or describes some other abstract concept or model."



Due to this absence of biometric standards, some institutions have been concerned of being tied into technologies they actually believed as not mature or even developmental.



• These include the desire for reducing the overall cost of deploying biometrics technologies and optimize the reliability of biometric systems.

• To reduce the risk of deploying solutions to biometric problems.

• To ensure in the area of encryption and file format, that the basic building blocks of biometric data management have been developed based on best practice by industry professionals.



“Standards ensure that, in the future, biometric technology will be developed and deployed in accordance with generally accepted principles of information technology.“

---- By Nanavati (2002 p. 278)


BRITISH BIOMETRICS STANDARDS

• BS ISO/IEC 19784-2:2007

• BS ISO/IEC 19795-2:2006

• BS ISO/IEC 24709-1:2007

• BS ISO/IEC 24709-2:2007


BS ISO/IEC 19784-2:2007

This standard defines the interface to an archive Biometric Function Provider (BFP). The interface assumes that the collected biometrics data will be managed as a database, irrespective of its physical realization. Crosier (2008, p. 24) defined the physical realization as "smartcards, token, memory sticks, files on hard drives and any other kind of memory can be handled via an abstraction layer presenting a database interface.)"


BS ISO/IEC 19795-2:2006

According to Shoniregun (2008, p. 25), this standard provides recommendations and requirements on collection of data, analysis as well as reporting specific to two types of evaluation (scenario evaluation and technology evaluation). BS ISO/IEC 19795-2:2006 further specifies the requirements in the development and full description of protocols for scenario and technology evaluations and also, in executing and reporting biometric evaluations.


BS ISO/IEC 24709-1:2007

"ISO/IEC 24709-1:2007 specifies the concepts, framework, test methods and criteria required to test conformity of biometric products claiming conformance to BioAPI (ISO/IEC 19784-1)." (www.iso.org). Crosier (2008, p. 25) stated ISO/IEC 24709-1:2007 specifies three conformance testing models which allows conformance testing of each of the BioAPIcomponents mainly a framework, an application and a BSP.


BS ISO/IEC 24709-2:2007

The standard BS ISO/IEC 247 defines a number of test assertions composed in the assertion language explicitly required in ISO/IEC 24709-1. The assertions allow a user to test the conformance of any biometric server producer (BSP) "that claims to be a conforming implementation of that International Standard" to ISO/IEC 19784-1 (BioAPI 2.0) (www.iso.org).


References1. Vashek Matyáš 1, Zdeněk Říha, “Security of Biometric Authentication Systems”, International Journal of Computer Information Systems and

Industrial Management Applications ISSN 2150-7988 Volume 3 (2011) pp. 174-184 © MIR Labs, www.mirlabs.net/ijcisim/index.html

2. Aleksandra Babich , “Biometric Authentication. Types of biometric identifiers” ,Haaga-Helia University of Applied Science.

3. Debnath Bhattacharyya, Rahul Ranjan,Farkhod Alisherov,, Choi Minkyu , “Biometric Authentication: A Review”, International Journal of u- and e-Service, Science and Technology, Vol. 2, No. 3, September, 2009.

4. James Wayman, Anil Jain, Davide Maltoni and Dario Maio, “An Introduction to Biometric Authentication Systems”,

5. Anil K. Jain, Karthik Nandakumar, “ Biometric Authentication: System Security and User Privacy” , Published by the IEEE Computer Society NOVEMBER 2012 , Page 87.


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