Facial Recognition

Facial recognition records the spatial geometry of distinguishing features of the face. Different vendors use different methods of facial recognition, however, all focus on measures of key features. Facial recognition templates are typically 83 to 1,000 bytes. Facial recognition technologies can encounter performance problems stemming from such factors as no cooperative behavior of the user, lighting, and other environmental variables. Facial recognition has been used in projects to identify card counters in casinos, shoplifters in stores, criminals in targeted urban areas, and terrorists overseas.

Voice Recognition

Voice or speaker recognition uses vocal characteristics to identify individuals using a pass-phrase. Voice recognition can be affected by such environmental factors as background noise. Additionally it is unclear whether the technologies actually recognize the voice or just the pronunciation of the pass-phrase (password) used. This technology has been the focus of considerable efforts on the part of the telecommunications industry and NSA, which continue to work on

improving reliability. A telephone or microphone can serve as a sensor, which makes it a relatively cheap and easily deployable technology.

Iris Scan

Iris scanning measures the iris pattern in the colored part of the eye, although the iris color has nothing to do with the biometric. Iris patterns are formed randomly. As a result, the iris patterns in your left and right eyes are different, and so are the iris patterns of identical-cal twins. Iris scan templates are typically around 256 bytes. Iris scanning can be used quickly for both identification and verification

Applications because of its large number of degrees of freedom. Current pilot programs and applications include ATMs (“Eye-TMs”), grocery stores (for checking out), and the few

Biometric identification refers to identifying an individual based on his/her distinguishing physiological and/or behavioural characteristics. As these characteristics are distinctive to each and every person, biometric identification is more reliable and capable than the traditional token based and knowledge based technologies differentiating between an authorized and a fraudulent person. This paper discusses the mainstream biometric technologies and the advantages and disadvantages of biometric technologies, their security issues and finally their applications in day today life.

INTRODUCTION:

“Biometrics” are automated methods of recognizing an individual based on their physical or behavioral characteristics. Some common commercial examples are fingerprint, face, iris, hand geometry, voice and dynamic signature. These, as well as many others, are in various stages of development and/or deployment. The type of biometric that is “best ” will vary significantly from one application to another. These methods of identification are preferred over traditional methods involving passwords and PIN numbers for various reasons: (i) the person to be identified is required to be physically present at the point-of-identification; (ii) identification based on biometric techniques obviates the need to remember a password or carry a token. 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.

A BIOMETRIC SYSTEM:

All biometric systems consist of three basic elements:

• Enrollment, or the process of collecting biometric samples from an individual, known as the enrollee, and the subsequent generation of his template.

• Templates, or the data representing the enrollee’s biometric.

• Matching, or the process of comparing a live biometric sample against one or many templates in the system’s database.

Enrollment

Enrollment is the crucial first stage for biometric authentication because enrollment generates a template that will be used for all subsequent matching. Typically, the device takes three samples of the same biometric and averages them to produce an enrollment template. Enrollment is complicated by the dependence of the performance of many biometric systems on the users’ familiarity with the biometric device because enrollment is usually the first time the user is exposed to the device. Environmental conditions also affect enrollment. Enrollment should take place under conditions similar to those expected during the routine matching process. For example, if voice verification is used in an environment where there is background noise, the system’s ability to match voices to enrolled templates depends on capturing these templates in the same environment. In addition to user and environmental issues, biometrics themselves change over time. Many biometric systems account for these changes by continuously averaging. Templates are averaged and updated each time the user attempts authentication.

Templates

As the data representing the enrollee’s biometric, the biometric device creates templates. The device uses a proprietary algorithm to extract “features” appropriate to that biometric from the enrollee’s samples. Templates are only a record of distinguishing features, sometimes called minutiae points, of a person’s biometric characteristic or trait. For example, templates are not an image or record of the actual fingerprint or voice. In basic terms, templates are numerical representations of key points taken from a person’s body. The template is usually small in terms of computer memory use, and this allows for quick processing, which is a hallmark of biometric authentication. The template must be stored somewhere so that subsequent templates, created when a user tries to access the system using a sensor, can be compared. Some biometric experts claim it is impossible to reverse-engineer, or recreate, a person’s print or image from the biometric template.

Matching

Matching is the comparison of two templates, the template produced at the time of enrollment (or at previous sessions, if there is continuous updating) with the one produced “on the spot” as a user tries to gain access by providing a biometric via a sensor. There are three ways a match can fail:

• Failure to enroll.

• False match.

• False nonmatch.

Failure to enroll (or acquire) is the failure of the technology to extract distinguishing features appropriate to that technology. For example, a small percentage of the population fails to enroll in fingerprint-based biometric authentication systems. Two reasons account for this failure: the individual’s fingerprints are not distinctive enough to be picked up by the system, or the distinguishing characteristics of the individual’s fingerprints have been altered because of the individual’s age or occupation, e.g., an elderly bricklayer.

In addition, the possibility of a false match (FM) or a false nonmatch (FNM) exists. These two terms are frequently misnomered “false acceptance” and “false rejection,” respectively, but these terms are application-dependent in meaning. FM and FNM are application-neutral terms to describe the matching process between a live sample and a biometric template. A false match occurs when a sample is incorrectly matched to a template in the database (i.e., an imposter is accepted). A false non-match occurs when a sample is incorrectly not matched to a truly matching template in the database (i.e., a legitimate match is denied). Rates for FM and FNM are calculated and used to make tradeoffs between security and convenience. For example, a heavy security emphasis errs on the side of denying legitimate matches and does not tolerate acceptance of imposters. A heavy emphasis on user convenience results in little tolerance for denying legitimate matches but will tolerate some acceptance of imposters.

BIOMETRIC TECHNOLOGIES:

The function of a biometric technologies authentication system is to facilitate controlled access to applications, networks, personal computers (PCs), and physical facilities. A biometric authentication system is essentially a method of establishing a person’s identity by comparing the binary code of a uniquely specific biological or physical characteristic to the binary code of an electronically stored characteristic called a biometric. The defining factor for implementing a biometric authentication system is that it cannot fall prey to hackers; it can’t be shared, lost, or guessed. Simply put, a biometric authentication system is an efficient way to replace the traditional password based authentication system. While there are many possible biometrics, at least eight mainstream biometric authentication technologies have been deployed or pilot-tested in applications in the public and private sectors and are grouped into two as given,

• Contact Biometric Technologies

  • fingerprint,

  • hand/finger geometry,

  • dynamic signature verification, and

  • keystroke dynamics

• Contactless Biometric Technologies

  • facial recognition,

  • voice recognition

  • iris scan,

  • retinal scan,

CONTACT BIOMETRIC TECHNOLOGIES:

For the purpose of this study, a biometric technology that requires an individual to make direct contact with an electronic device (scanner) will be referred to as a contact biometric. Given that the very nature of a contact biometric is that a person desiring access is required to make direct contact with an electronic device in order to attain logical or physical access. Because of the inherent need of a person to make direct contact, many people have come to consider a contact biometric to be a technology that encroaches on personal space and to be intrusive to personal privacy.

Fingerprint

The fingerprint biometric is an automated digital version of the old ink-and-paper method used for more than a century for identification, primarily by law enforcement agencies. The biometric device involves users placing their finger on a platen for the print to be read. The minutiae are then extracted by the vendor’s algorithm, which also makes a fingerprint pattern analysis. Fingerprint template sizes are typically 50 to 1,000 bytes. Fingerprint biometrics currently have three main application arenas: large-scale Automated Finger Imaging Systems (AFIS) generally used for law enforcement purposes, fraud prevention in entitlement pro-grams, and physical and computer access.

Hand/Finger Geometry

Hand or finger geometry is an automated measurement of many dimensions of the hand and fingers. Neither of these methods takes actual prints of the palm or fingers. Only the spatial geometry is examined as the user puts his hand on the sensor’s surface and uses guiding poles between the fingers to properly place the hand and initiate the reading. Hand geometry templates are typically 9 bytes, and finger geometry templates are 20 to 25 bytes. Finger geometry usually measures two or three fingers. Hand geometry is a well-developed technology that has been thoroughly field-tested and is easily accepted by users.

Dynamic Signature Verification

Dynamic signature verification is an automated method of examining an individual’s signature. This technology examines such dynamics as speed, direction, and pressure of writing; the time that the stylus is in and out of contact with the “paper”; the total time taken to make the signature; and where the stylus is raised from and lowered onto the “paper.” Dynamic signature verification templates are typically 50 to 300 bytes.

Keystroke Dynamics

Keystroke dynamics is an automated method of examining an individual’s keystrokes on a keyboard. This technology examines such dynamics as speed and pressure, the total time of typing a particular password, and the time a user takes between hitting certain keys. This technology’s algorithms are still being developed to improve robustness and distinctiveness. One potentially useful application that may emerge is computer access, where this biometric could be used to verify the computer user’s identity continuously.

CONTACTLESS BIOMETRIC TECHNOLOGIES:

A contactless biometric can either come in the form of a passive (biometric device continuously monitors for the correct activation frequency) or active (user initiates activation at will) biometric. In either event, authentication of the user biometric should not take place until the user voluntarily agrees to present the biometric for sampling. A contactless biometric can be used to verify a persons identity and offers at least two dimension that contact biometric technologies cannot match. A contactless biometric is one that does not require undesirable contact in order to extract the required data sample of the biological characteristic and in that respect a contactless biometric is most adaptable to people of variable ability levels.

Facial Recognition

Facial recognition records the spatial geometry of distinguishing features of the face. Different vendors use different methods of facial recognition, however, all focus on measures of key features. Facial recognition templates are typically 83 to 1,000 bytes. Facial recognition technologies can encounter performance problems stemming from such factors as no cooperative behavior of the user, lighting, and other environmental variables. Facial recognition has been used in projects to identify card counters in casinos, shoplifters in stores, criminals in targeted urban areas, and terrorists overseas.

Voice Recognition

Voice or speaker recognition uses vocal characteristics to identify individuals using a pass-phrase. Voice recognition can be affected by such environmental factors as background noise. Additionally it is unclear whether the technologies actually recognize the voice or just the pronunciation of the pass-phrase (password) used. This technology has been the focus of considerable efforts on the part of the telecommunications industry and NSA, which continue to work on

improving reliability. A telephone or microphone can serve as a sensor, which makes it a relatively cheap and easily deployable technology.

Iris Scan

Iris scanning measures the iris pattern in the colored part of the eye, although the iris color has nothing to do with the biometric. Iris patterns are formed randomly. As a result, the iris patterns in your left and right eyes are different, and so are the iris patterns of identical-cal twins. Iris scan templates are typically around 256 bytes. Iris scanning can be used quickly for both identification and verification

Applications because of its large number of degrees of freedom. Current pilot programs and applications include ATMs (“Eye-TMs”), grocery stores (for checking out), and the few I

Templates

As the data representing the enrollee’s biometric, the biometric device creates templates. The device uses a proprietary algorithm to extract “features” appropriate to that biometric from the enrollee’s samples. Templates are only a record of distinguishing features, sometimes called minutiae points, of a person’s biometric characteristic or trait. For example, templates are not an image or record of the actual fingerprint or voice. In basic terms, templates are numerical representations of key points taken from a person’s body. The template is usually small in terms of computer memory use, and this allows for quick processing, which is a hallmark of biometric authentication. The template must be stored somewhere so that subsequent templates, created when a user tries to access the system using a sensor, can be compared. Some biometric experts claim it is impossible to reverse-engineer, or recreate, a person’s print or image from the biometric template.

Matching

Matching is the comparison of two templates, the template produced at the time of enrollment (or at previous sessions, if there is continuous updating) with the one produced “on the spot” as a user tries to gain access by providing a biometric via a sensor. There are three ways a match can fail:

• Failure to enroll.

• False match.

• False nonmatch.

Failure to enroll (or acquire) is the failure of the technology to extract distinguishing features appropriate to that technology. For example, a small percentage of the population fails to enroll in fingerprint-based biometric authentication systems. Two reasons account for this failure: the individual’s fingerprints are not distinctive enough to be picked up by the system, or the distinguishing characteristics of the individual’s fingerprints have been altered because of the individual’s age or occupation, e.g., an elderly bricklayer.

In addition, the possibility of a false match (FM) or a false nonmatch (FNM) exists. These two terms are frequently misnomered “false acceptance” and “false rejection,” respectively, but these terms are application-dependent in meaning. FM and FNM are application-neutral terms to describe the matching process between a live sample and a biometric template. A false match occurs when a sample is incorrectly matched to a template in the database (i.e., an imposter is accepted). A false non-match occurs when a sample is incorrectly not matched to a truly matching template in the database (i.e., a legitimate match is denied). Rates for FM and FNM are calculated and used to make tradeoffs between security and convenience. For example, a heavy security emphasis errs on the side of denying legitimate matches and does not tolerate acceptance of imposters. A heavy emphasis on user convenience results in little tolerance for denying legitimate matches but will tolerate some acceptance of imposters.

BIOMETRIC TECHNOLOGIES:

The function of a biometric technologies authentication system is to facilitate controlled access to applications, networks, personal computers (PCs), and physical facilities. A biometric authentication system is essentially a method of establishing a person’s identity by comparing the binary code of a uniquely specific biological or physical characteristic to the binary code of an electronically stored characteristic called a biometric. The defining factor for implementing a biometric authentication system is that it cannot fall prey to hackers; it can’t be shared, lost, or guessed. Simply put, a biometric authentication system is an efficient way to replace the traditional password based authentication system. While there are many possible biometrics, at least eight mainstream biometric authentication technologies have been deployed or pilot-tested in applications in the public and private sectors and are grouped into two as given,

• Contact Biometric Technologies

  • fingerprint,

  • hand/finger geometry,

  • dynamic signature verification, and

  • keystroke dynamics

• Contactless Biometric Technologies

  • facial recognition,

  • voice recognition

  • iris scan,

  • retinal scan,

CONTACT BIOMETRIC TECHNOLOGIES:

For the purpose of this study, a biometric technology that requires an individual to make direct contact with an electronic device (scanner) will be referred to as a contact biometric. Given that the very nature of a contact biometric is that a person desiring access is required to make direct contact with an electronic device in order to attain logical or physical access. Because of the inherent need of a person to make direct contact, many people have come to consider a contact biometric to be a technology that encroaches on personal space and to be intrusive to personal privacy.

Fingerprint

The fingerprint biometric is an automated digital version of the old ink-and-paper method used for more than a century for identification, primarily by law enforcement agencies. The biometric device involves users placing their finger on a platen for the print to be read. The minutiae are then extracted by the vendor’s algorithm, which also makes a fingerprint pattern analysis. Fingerprint template sizes are typically 50 to 1,000 bytes. Fingerprint biometrics currently have three main application arenas: large-scale Automated Finger Imaging Systems (AFIS) generally used for law enforcement purposes, fraud prevention in entitlement pro-grams, and physical and computer access.

Hand/Finger Geometry

Hand or finger geometry is an automated measurement of many dimensions of the hand and fingers. Neither of these methods takes actual prints of the palm or fingers. Only the spatial geometry is examined as the user puts his hand on the sensor’s surface and uses guiding poles between the fingers to properly place the hand and initiate the reading. Hand geometry templates are typically 9 bytes, and finger geometry templates are 20 to 25 bytes. Finger geometry usually measures two or three fingers. Hand geometry is a well-developed technology that has been thoroughly field-tested and is easily accepted by users.

Dynamic Signature Verification

Dynamic signature verification is an automated method of examining an individual’s signature. This technology examines such dynamics as speed, direction, and pressure of writing; the time that the stylus is in and out of contact with the “paper”; the total time taken to make the signature; and where the stylus is raised from and lowered onto the “paper.” Dynamic signature verification templates are typically 50 to 300 bytes.

Keystroke Dynamics

Keystroke dynamics is an automated method of examining an individual’s keystrokes on a keyboard. This technology examines such dynamics as speed and pressure, the total time of typing a particular password, and the time a user takes between hitting certain keys. This technology’s algorithms are still being developed to improve robustness and distinctiveness. One potentially useful application that may emerge is computer access, where this biometric could be used to verify the computer user’s identity continuously.

CONTACTLESS BIOMETRIC TECHNOLOGIES:

A contactless biometric can either come in the form of a passive (biometric device continuously monitors for the correct activation frequency) or active (user initiates activation at will) biometric. In either event, authentication of the user biometric should not take place until the user voluntarily agrees to present the biometric for sampling. A contactless biometric can be used to verify a persons identity and offers at least two dimension that contact biometric technologies cannot match. A contactless biometric is one that does not require undesirable contact in order to extract the required data sample of the biological characteristic and in that respect a contactless biometric is most adaptable to people of variable ability levels.

Facial Recognition

Facial recognition records the spatial geometry of distinguishing features of the face. Different vendors use different methods of facial recognition, however, all focus on measures of key features. Facial recognition templates are typically 83 to 1,000 bytes. Facial recognition technologies can encounter performance problems stemming from such factors as no cooperative behavior of the user, lighting, and other environmental variables. Facial recognition has been used in projects to identify card counters in casinos, shoplifters in stores, criminals in targeted urban areas, and terrorists overseas.

Voice Recognition

Voice or speaker recognition uses vocal characteristics to identify individuals using a pass-phrase. Voice recognition can be affected by such environmental factors as background noise. Additionally it is unclear whether the technologies actually recognize the voice or just the pronunciation of the pass-phrase (password) used. This technology has been the focus of considerable efforts on the part of the telecommunications industry and NSA, which continue to work on

improving reliability. A telephone or microphone can serve as a sensor, which makes it a relatively cheap and easily deployable technology.

Iris Scan

Iris scanning measures the iris pattern in the colored part of the eye, although the iris color has nothing to do with the biometric. Iris patterns are formed randomly. As a result, the iris patterns in your left and right eyes are different, and so are the iris patterns of identical-cal twins. Iris scan templates are typically around 256 bytes. Iris scanning can be used quickly for both identification and verification

Applications because of its large number of degrees of freedom. Current pilot programs and applications include ATMs (“Eye-TMs”), grocery stores (for checking out), and the few

BIOMETRIC TECHNOLOGIES:

The function of a biometric technologies authentication system is to facilitate controlled access to applications, networks, personal computers (PCs), and physical facilities. A biometric authentication system is essentially a method of establishing a person’s identity by comparing the binary code of a uniquely specific biological or physical characteristic to the binary code of an electronically stored characteristic called a biometric. The defining factor for implementing a biometric authentication system is that it cannot fall prey to hackers; it can’t be shared, lost, or guessed. Simply put, a biometric authentication system is an efficient way to replace the traditional password based authentication system. While there are many possible biometrics, at least eight mainstream biometric authentication technologies have been deployed or pilot-tested in applications in the public and private sectors and are grouped into two as given,

• Contact Biometric Technologies

  • fingerprint,

  • hand/finger geometry,

  • dynamic signature verification, and

  • keystroke dynamics

• Contactless Biometric Technologies

  • facial recognition,

  • voice recognition

  • iris scan,

  • retinal scan,

CONTACT BIOMETRIC TECHNOLOGIES:

For the purpose of this study, a biometric technology that requires an individual to make direct contact with an electronic device (scanner) will be referred to as a contact biometric. Given that the very nature of a contact biometric is that a person desiring access is required to make direct contact with an electronic device in order to attain logical or physical access. Because of the inherent need of a person to make direct contact, many people have come to consider a contact biometric to be a technology that encroaches on personal space and to be intrusive to personal privacy.

Fingerprint

The fingerprint biometric is an automated digital version of the old ink-and-paper method used for more than a century for identification, primarily by law enforcement agencies. The biometric device involves users placing their finger on a platen for the print to be read. The minutiae are then extracted by the vendor’s algorithm, which also makes a fingerprint pattern analysis. Fingerprint template sizes are typically 50 to 1,000 bytes. Fingerprint biometrics currently have three main application arenas: large-scale Automated Finger Imaging Systems (AFIS) generally used for law enforcement purposes, fraud prevention in entitlement pro-grams, and physical and computer access.

Hand/Finger Geometry

Hand or finger geometry is an automated measurement of many dimensions of the hand and fingers. Neither of these methods takes actual prints of the palm or fingers. Only the spatial geometry is examined as the user puts his hand on the sensor’s surface and uses guiding poles between the fingers to properly place the hand and initiate the reading. Hand geometry templates are typically 9 bytes, and finger geometry templates are 20 to 25 bytes. Finger geometry usually measures two or three fingers. Hand geometry is a well-developed technology that has been thoroughly field-tested and is easily accepted by users.

Dynamic Signature Verification

Dynamic signature verification is an automated method of examining an individual’s signature. This technology examines such dynamics as speed, direction, and pressure of writing; the time that the stylus is in and out of contact with the “paper”; the total time taken to make the signature; and where the stylus is raised from and lowered onto the “paper.” Dynamic signature verification templates are typically 50 to 300 bytes.

Keystroke Dynamics

Keystroke dynamics is an automated method of examining an individual’s keystrokes on a keyboard. This technology examines such dynamics as speed and pressure, the total time of typing a particular password, and the time a user takes between hitting certain keys. This technology’s algorithms are still being developed to improve robustness and distinctiveness. One potentially useful application that may emerge is computer access, where this biometric could be used to verify the computer user’s identity continuously.

CONTACTLESS BIOMETRIC TECHNOLOGIES:

A contactless biometric can either come in the form of a passive (biometric device continuously monitors for the correct activation frequency) or active (user initiates activation at will) biometric. In either event, authentication of the user biometric should not take place until the user voluntarily agrees to present the biometric for sampling. A contactless biometric can be used to verify a persons identity and offers at least two dimension that contact biometric technologies cannot match. A contactless biometric is one that does not require undesirable contact in order to extract the required data sample of the biological characteristic and in that respect a contactless biometric is most adaptable to people of variable ability levels.

Facial Recognition

Facial recognition records the spatial geometry of distinguishing features of the face. Different vendors use different methods of facial recognition, however, all focus on measures of key features. Facial recognition templates are typically 83 to 1,000 bytes. Facial recognition technologies can encounter performance problems stemming from such factors as no cooperative behavior of the user, lighting, and other environmental variables. Facial recognition has been used in projects to identify card counters in casinos, shoplifters in stores, criminals in targeted urban areas, and terrorists overseas.

Voice Recognition

Voice or speaker recognition uses vocal characteristics to identify individuals using a pass-phrase. Voice recognition can be affected by such environmental factors as background noise. Additionally it is unclear whether the technologies actually recognize the voice or just the pronunciation of the pass-phrase (password) used. This technology has been the focus of considerable efforts on the part of the telecommunications industry and NSA, which continue to work on

improving reliability. A telephone or microphone can serve as a sensor, which makes it a relatively cheap and easily deployable technology.

Iris Scan

Iris scanning measures the iris pattern in the colored part of the eye, although the iris color has nothing to do with the biometric. Iris patterns are formed randomly. As a result, the iris patterns in your left and right eyes are different, and so are the iris patterns of identical-cal twins. Iris scan templates are typically around 256 bytes. Iris scanning can be used quickly for both identification and verification

Applications because of its large number of degrees of freedom. Current pilot programs and applications include ATMs (“Eye-TMs”), grocery stores (for checking out), and the few

Fingerprint

The fingerprint biometric is an automated digital version of the old ink-and-paper method used for more than a century for identification, primarily by law enforcement agencies. The biometric device involves users placing their finger on a platen for the print to be read. The minutiae are then extracted by the vendor’s algorithm, which also makes a fingerprint pattern analysis. Fingerprint template sizes are typically 50 to 1,000 bytes. Fingerprint biometrics currently have three main application arenas: large-scale Automated Finger Imaging Systems (AFIS) generally used for law enforcement purposes, fraud prevention in entitlement pro-grams, and physical and computer access.

Hand/Finger Geometry

Hand or finger geometry is an automated measurement of many dimensions of the hand and fingers. Neither of these methods takes actual prints of the palm or fingers. Only the spatial geometry is examined as the user puts his hand on the sensor’s surface and uses guiding poles between the fingers to properly place the hand and initiate the reading. Hand geometry templates are typically 9 bytes, and finger geometry templates are 20 to 25 bytes. Finger geometry usually measures two or three fingers. Hand geometry is a well-developed technology that has been thoroughly field-tested and is easily accepted by users.

Dynamic Signature Verification

Dynamic signature verification is an automated method of examining an individual’s signature. This technology examines such dynamics as speed, direction, and pressure of writing; the time that the stylus is in and out of contact with the “paper”; the total time taken to make the signature; and where the stylus is raised from and lowered onto the “paper.” Dynamic signature verification templates are typically 50 to 300 bytes.

Keystroke Dynamics

Keystroke dynamics is an automated method of examining an individual’s keystrokes on a keyboard. This technology examines such dynamics as speed and pressure, the total time of typing a particular password, and the time a user takes between hitting certain keys. This technology’s algorithms are still being developed to improve robustness and distinctiveness. One potentially useful application that may emerge is computer access, where this biometric could be used to verify the computer user’s identity continuously.

CONTACTLESS BIOMETRIC TECHNOLOGIES:

A contactless biometric can either come in the form of a passive (biometric device continuously monitors for the correct activation frequency) or active (user initiates activation at will) biometric. In either event, authentication of the user biometric should not take place until the user voluntarily agrees to present the biometric for sampling. A contactless biometric can be used to verify a persons identity and offers at least two dimension that contact biometric technologies cannot match. A contactless biometric is one that does not require undesirable contact in order to extract the required data sample of the biological characteristic and in that respect a contactless biometric is most adaptable to people of variable ability levels.

Facial Recognition

Facial recognition records the spatial geometry of distinguishing features of the face. Different vendors use different methods of facial recognition, however, all focus on measures of key features. Facial recognition templates are typically 83 to 1,000 bytes. Facial recognition technologies can encounter performance problems stemming from such factors as no cooperative behavior of the user, lighting, and other environmental variables. Facial recognition has been used in projects to identify card counters in casinos, shoplifters in stores, criminals in targeted urban areas, and terrorists overseas.

Voice Recognition

Voice or speaker recognition uses vocal characteristics to identify individuals using a pass-phrase. Voice recognition can be affected by such environmental factors as background noise. Additionally it is unclear whether the technologies actually recognize the voice or just the pronunciation of the pass-phrase (password) used. This technology has been the focus of considerable efforts on the part of the telecommunications industry and NSA, which continue to work on

improving reliability. A telephone or microphone can serve as a sensor, which makes it a relatively cheap and easily deployable technology.

Iris Scan

Iris scanning measures the iris pattern in the colored part of the eye, although the iris color has nothing to do with the biometric. Iris patterns are formed randomly. As a result, the iris patterns in your left and right eyes are different, and so are the iris patterns of identical-cal twins. Iris scan templates are typically around 256 bytes. Iris scanning can be used quickly for both identification and verification

Applications because of its large number of degrees of freedom. Current pilot programs and applications include ATMs (“Eye-TMs”), grocery stores (for checking out), and the few

Facial Recognition

Facial recognition records the spatial geometry of distinguishing features of the face. Different vendors use different methods of facial recognition, however, all focus on measures of key features. Facial recognition templates are typically 83 to 1,000 bytes. Facial recognition technologies can encounter performance problems stemming from such factors as no cooperative behavior of the user, lighting, and other environmental variables. Facial recognition has been used in projects to identify card counters in casinos, shoplifters in stores, criminals in targeted urban areas, and terrorists overseas.

Voice Recognition

Voice or speaker recognition uses vocal characteristics to identify individuals using a pass-phrase. Voice recognition can be affected by such environmental factors as background noise. Additionally it is unclear whether the technologies actually recognize the voice or just the pronunciation of the pass-phrase (password) used. This technology has been the focus of considerable efforts on the part of the telecommunications industry and NSA, which continue to work on

improving reliability. A telephone or microphone can serve as a sensor, which makes it a relatively cheap and easily deployable technology.

Iris Scan

Iris scanning measures the iris pattern in the colored part of the eye, although the iris color has nothing to do with the biometric. Iris patterns are formed randomly. As a result, the iris patterns in your left and right eyes are different, and so are the iris patterns of identical-cal twins. Iris scan templates are typically around 256 bytes. Iris scanning can be used quickly for both identification and verification

Applications because of its large number of degrees of freedom. Current pilot programs and applications include ATMs (“Eye-TMs”), grocery stores (for checking out), and the few International Airports (physical access).

Retinal Scan

Retinal scans measure the blood vessel patterns in the back of the eye. Retinal scan templates are typically 40 to 96 bytes. Because users perceive the technology to be somewhat intrusive, retinal scanning has not gained popularity with end-users. The device involves a light source shined into the eye of a user who must be standing very still within inches of the device. Because the retina can change with certain medical conditions, such as pregnancy, high blood pressure, and AIDS, this biometric might have the potential to reveal more information than just an individual’s identity.

Emerging biometric technologies:

Many inventors, companies, and universities continue to search the frontier for the next biometric that shows potential of becoming the best. Emerging biometric is a biometric that is in the infancy stages of proven technological maturation. Once proven, an emerging biometric will evolve in to that of an established biometric. Such types of emerging technologies are the following:

• Brainwave Biometric

• DNA Identification

• Vascular Pattern Recognition

• Body Odor Recognition

• Fingernail Bed Recognition

• Gait Recognition

• Handgrip Recognition

• Ear Pattern Recognition

• Body Salinity Identification

• Infrared Fingertip Imaging & Pattern Recognition

SECURITY ISSUES:

The most common standardized encryption method used to secure a company’s infrastructure is the Public Key Infrastructure (PKI) approach. This approach consists of two keys with a binary string ranging in size from 1024-bits to 2048-bits, the first key is a public key (widely known) and the second key is a private key (only known by the owner). However, the PKI must also be stored and inherently it too can fall prey to the same authentication limitation of a password, PIN, or token. It too can be guessed, lost, stolen, shared, hacked, or circumvented; this is even further justification for a biometric authentication system. Because of the structure of the technology industry, making biometric security a feature of embedded systems, such as cellular phones, may be simpler than adding similar features to PCs. Unlike the personal computer, the cell phone is a fixed-purpose device. To successfully incorporate Biometrics, cell-phone developers need not gather support from nearly as many groups as PC-application developers must.

Security has always been a major concern for company executives and information technology professionals of all entities. A biometric authentication system that is correctly implemented can provide unparalleled security, enhanced convenience, heightened accountability, superior fraud detection, and is extremely effective in discouraging fraud. Controlling access to logical and physical assets of a company is not the only concern that must be addressed. Companies, executives, and security managers must also take into account security of the biometric data (template). There are many urban biometric legends about cutting off someone finger or removing a body part for the purpose of gain access. This is not true for once the blood supply of a body part is taken away, the unique details of that body part starts to deteriorate within minutes. Hence the unique details of the severed body part(s) is no longer in any condition to function as an acceptable input for scanners.

The best overall way to secure an enterprise infrastructure, whether it be small or large is to use a smart card. A smart card is a portable device with an embedded central processing unit (CPU). The smart card can either be fashioned to resemble a credit card, identification card, radio frequency identification (RFID), or a Personal Computer Memory Card International Association (PCMCIA) card. The smart card can be used to store data of all types, but it is commonly used to store encrypted data, human resources data, medical data, financial data, and biometric data (template). The smart card can be access via a card reader, PCMCIA slot, or proximity reader. In most biometric-security applications, the system itself determines the identity of the person who presents himself to the system. Usually, the identity is supplied to the system, often by presenting a machine-readable ID card, and then the system asked to confirm. This problem is "one-to- one matching." Today's PCs can conduct a one-to-one match in, at most, a few seconds. One-to-one matching differs significantly from one-to-many matching. In a system that stores a million sets of prints, a one-to-many match requires comparing the presented fingerprint with 10 million prints (1 million sets times 10 prints/set). A smart card is a must when implementing a biometric authentication system; only by the using a smart card can an organization satisfy all security and legal requirements. Smart cards possess the basic elements of a computer (interface, processor, and storage), and are therefore very capable of performing authentication functions right on the card.

The function of performing authentication within the confines of the card is known as ‘Matching on the Card (MOC)’. From a security prospective MOC is ideal as the biometric template, biometric sampling and associated algorithms never leave the card and as such cannot be intercepted or spoofed by others (Smart Card Alliance). The problem with smart cards is the public-key infrastructure certificates built into card does not solve the problem of someone stealing the card or creating one. A TTP (Trusted Third Party) can be used to verify the authenticity of a card via an encrypted MAC (Media Access Control).

CULTURAL BARRIERS/PERCEPTIONS:

People as diverse as those of variable abilities are subject to many barriers, theories, concepts, and practices that stem from the relative culture (i.e. stigma, dignity or heritage) and perceptions (i.e. religion or philosophical) of the international community. These factors are so great that they could encompass a study of their own. To that end, it is also theorized that to a certain degree that the application of diversity factors from current theories, concepts, and practices may be capable of providing a sturdy framework to the management of employees with disabilities. Moreover, it has been implied that the term diversity is a synonymous reflection of the initiatives and objectives of affirmative action policies. The concept of diversity in the workplace actually refers to the differences embodied by the workforce members at large. The differences between all employees in the workforce can be equated to those employees of different or diverse ethnic origin, racial descent, gender, sexual orientation, chronological maturity, and ability; in effect minorities.

ADVANTAGES OF BIOMETRIC TECHNOLOGIES:

Biometric technologies can be applied to areas requiring logical access solutions, and it can be used to access applications, personal computers, networks, financial accounts, human resource records, the telephone system, and invoke customized profiles to enhance the mobility of the disabled. In a business-to-business scenario, the biometric authentication system can be linked to the business processes of a company to increase accountability of financial systems, vendors, and supplier transactions; the results can be extremely beneficial.

The global reach of the Internet has made the services and products of a company available 24/7, provided the consumer has a user name and password to login. In many cases the consumer may have forgotten his/her user name, password, or both. The consumer must then take steps to retrieve or reset his/her lost or forgotten login information. By implementing a biometric authentication system consumers can opt to register their biometric trait or smart card with a company’s business-to-consumer e-commerce environment, which will allow a consumer to access their account and pay for goods and services (e-commerce). The benefit is that a consumer will never lose or forget his/her user name or password, and will be able to conduct business at their convenience. A biometric authentications system can be applied to areas requiring physical access solutions, such as entry into a building, a room, a safe or it may be used to start a motorized vehicle. Additionally, a biometric authentication system can easily be linked to a computer-based application used to monitor time and attendance of employees as they enter and leave company facilities. In short, contactless biometrics can and do lend themselves to people of all ability levels.

DISADVANTAGES OF BIOMETRIC TECHNOLOGIES:

Some people, especially those with disabilities may have problems with contact biometrics. Not because they do not want to use it, but because they endure a disability that either prevents them from maneuvering into a position that will allow them to make use the biometric or because the biometric authentication system (solution) is not adaptable to the user. For example, if the user is blind a voice biometric may be more appropriate.

BIOMETRIC APPLICATIONS:

Most biometric applications fall into one of nine general categories:

• Financial services (e.g., ATMs and kiosks).

• Immigration and border control (e.g., points of entry, precleared frequent travelers, passport and visa issuance, asylum cases).

• Social services (e.g., fraud prevention in entitlement programs).

• Health care (e.g., security measure for privacy of medical records).

• Physical access control (e.g., institutional, government, and residential).

• Time and attendance (e.g., replacement of time punch card).

• Computer security (e.g., personal computer access, network access, Internet use, e-commerce, e-mail, encryption).

• Telecommunications (e.g., mobile phones, call center technology, phone cards, televised shopping).

• Law enforcement (e.g., criminal investigation, national ID, driver’s license, correctional institutions/prisons, home confinement, smart gun).

CONCLUSION:

Currently, there exist a gap between the number of feasible biometric projects and knowledgeable experts in the field of biometric technologies. The post September 11 th, 2002 attack (a.k.a. 9-11) on the World Trade Center has given rise to the knowledge gap. Post 9-11 ma