Biometrics

Biometrics (ancient Greek: bios life, metron measure) refers to two very different fields of study and application. The first, which is the older and is used in biological studies, is the collection, synthesis, analysis and management of data in biology. Biometrics in reference to biological sciences, or biostatistics, has been studied since the early twentieth century.



More recently and incongruously, the term's meaning has been broadened to include the study of methods for uniquely recognizing humans based upon one or more intrinsic physical or behavioral traits.
Overview
Biometrics are used to identify the input sample when compared to a template, used in cases to identify specific people by certain characteristics.

possession-based
using one specific "token" such as a security tag or a card
knowledge-based
the use of a code or password.
Standard validation systems often use multiple inputs of samples for sufficient validation, such as particular characteristics of the sample. This intends to enhance security as multiple different samples are required such as security tags and codes and sample dimensions

Biometric characteristics can be divided in two main classes, as represented in figure on the right:

physiological are related to the shape of the body. The oldest traits, that have been used for more than 100 years, are fingerprints. Other examples are face recognition, hand geometry and iris recognition.
behavioral are related to the behavior of a person. The first characteristic to be used, still widely used today, is the signature. More modern approaches are the study of keystroke dynamics and of voice.[citation needed]
Recently, a new trend has been developed that merges human perception to computer database in a brain-machine interface. This approach has been referred to as cognitive biometrics. Cognitive biometrics is based on specific responses of the brain to stimuli which could be used to trigger a computer database search. Currently, cognitive biometrics systems are being developed to use brain response to odor stimuli [3], facial perception [4] and mental performance [5] for search at ports and high security areas. These systems are based on use of functional transcranial Doppler (fTCD) and functional transcranial Doppler spectroscopy (fTCDS) [6] to obtain brain responses, which are used to match a target odor, a target face or target performance profile stored in a computer database. Thus, the precision of human perception provides the data to match that stored in the computer with improve sensitivity of the system.

Strictly speaking, voice is also a physiological trait because every person has a different pitch, but voice recognition is mainly based on the study of the way a person speaks, commonly classified as behavioral.

Other biometric strategies are being developed such as those based on gait (way of walking), retina, hand veins, finger veins, ear canal, facial thermogram, DNA, odor and scent, palm prints and footprints.


[edit] Odor and Scent Cognitive Biometric Systems
Odor evaluation is important in criminal prosecution and defense. Blood hounds and other dogs have been used to identify individuals by their scent trails. Dogs are first offered a reference article, such as a handkerchief, hat, or an article of clothing.[7] This scent evidence is usually admissible in court. It's employed similarly to finger print identification. [8] The latter is premised on the alleged factuality of the "individual odor theory," which hold that each person has a unique scent that can be identified by the dog and related back to a specific individual. High courts have accepted the performance of canine scent identification, even when it is claimed that they are detecting the scent of a specific individual at the scene of a crime nearly 2 years after the crime was committed as discussed in the case State v. Eugene Wiley Case No. 8001659, 18th Judicial Circuit, Brevard County Fla. (1982). Canine scent identification is not without problems; juries have convicted defendants almost solely on the basis of odor evaluation evidence which has subsequently been shown to be unreliable, even fraudulent, as in the case State v. Kevin Roscoe, CR-127656, 11-20-90, Maricopa County, Arizona Superior Court, Judge Paulson. It is therefore imperative that further research studies of the abilities of such scenting dogs be undertaken. Especially, the ability to scent match odors from individuals to handled objects, under controlled laboratory conditions [9];[10] However, in some studies dogs have proven capable of performing such scent matching tasks at levels greater than chance, their error rates are seldom more than 10 to 20% [11] Errors may also be introduced by the interpretation of the behavioral response of the dog. What is probably lacking is an objective physiologic correlate of scent matching odors in canine detectives. The latter has the subject matter current research. There is thus ample evidence that in primates olfactory memory has several unique characteristics, the most striking being its resistance to decay over long intervals, suggesting a specialized memory system. However, investigations into the neural substrates of human olfactory memory have been limited. Previous positron emission tomography (PET) studies have shown significant regional cerebral blood flow (rCBF) increases during olfactory stimulation: unilateral in the right orbitofrontal cortex (OFC), and bilaterally in the inferior frontal and temporal lobes (piriform cortex) [12]. A new approach that uses noninvasive transcranial Doppler ultrasound to measure mean blood flow velocities in human and canine subjects during odor presentation is currently being evaluated. The target odor such as bomb making materials (e.g. TNT) or noxious chemicals elicit are first committed to memory in human or canine detectors. A area wide search such as at a seaport or at an airport could produce a matching odor, that triggers pattern recognition by computer. The latter is a brain-machine interface for odor recognition such as that described in United States Patent No. 6,663,571.[citation needed]


[edit] Facial Cognitive Biometric Systems
The analysis and recognition of facial features is a tool used in the detection of criminals and undesirables. Conventional biometric methods introduced to improve security are mainly based on cross matching the face of the person with that recorded in their databases. At present, the data is static and would not, for example, identify suspects with cosmetic or plastic surgery modification of their faces to escape identification. However, it is possible to train persons that could be referred to as "face-minders", to memorized faces of suspects on a watch-list, by way of example. Trainees could acquire skills of cross-matching key features of faces of persons seen at the ports as compared to that in the forensic facial database. However to be effective, subjective judgment must be replaced with objective physiologic correlates of good matches. This will require objective online detection of physiologic variables, suggestive of facial memory involvement and cross matching the online variables to expected variables, for the particular face involved. Online brain imaging adapted for use for such applications include electrophysiological techniques and transcranial Doppler ultrasound. One such brain-machine interface method based on functional transcranial Doppler spectroscopy (fTCDS), detects the presence of an equivalent to cortical long-term potentiation (CLTP), in the left middle cerebral artery [13] in male face minders and triggers a search for a matching face, to be reviewed by other observers as described in United States Patent Application No. 20040158155.


[edit] Cognitive Performance Biometric Systems
Task performance using general intelligence must elicit responses in neural anatomic structures for processing of the information. In task requiring general intelligence there is the necessity of keeping several conceptual formulations in mind such as during Raven's Progressive Matrices (RPM), and is itself a working memory function [14] involving prefrontal cortex [15]. Basso and others demonstrated that post-rolandic structures may be more critical for this general task as shown in patients with brain lesions [16]. Evidence obtained in normal subjects using positron emission tomography studies have shown that high g tasks do not show diffuse recruitment of multiple brain regions, instead they are associated with selective recruitment of lateral prefrontal cortex in one or both hemispheres [17].

It has been shown that working memory is typically associated with activations in the prefrontal cortex (PFC), anterior cingulate, parietal and occipital regions. These brain areas received blood supply from the middle cerebral arteries. Two fundamental working-memory processes have been identified: the passive maintenance of information in short-term memory and the active manipulation of this information [18].

In young subjects, studies using RPM tasks showed areas of regional CBF activation that comprised inferolateral temporal cortex including the fusiform gyrus bilaterally, and the middle temporal gyrus on the left, portions of the left medial temporal cortex including the parahippocampal gyrus, the left inferior parietal lobule, and the cerebellum[19]. The identified anatomic structures (except for the cerebellum) derive major blood supply from the middle cerebral artery. In a study, using functional transcranial Doppler (fTCD), Njemanze demonstrated that for successful resolution of RPM tasks, females used a left hemisphere strategy while males used the right hemisphere. The latter implies that general intelligence is associated with neural systems within one hemisphere that are accessible to a variety of cognitive processes. It was demonstrated that bi-hemispheric activation was associated with Wrong ANSWER, which may suggest that, increasing level of task difficulty is associated with diverse pattern of neural activation due to broad sampling of all major cognitive functions [20]. Njemanze postulated that, successful RPM problem-solving employs a discrete knowledge strategy (DKS), that selects neural pathways represented in one hemisphere. While unsuccessful outcome implicates a non-discrete knowledge strategy (nDKS). RPM paradigm could be viewed as a working memory task.

This suggests that the DKS model may have a correlate in mnemonic operations. In other words, DKS model may have a discrete knowledge base (DKB) of essential components needed for task resolution, while for nDKS, DKB is absent, and hence a "global" or bi-hemispheric search occurs. Based on these findings, a brain-machine interface system was designed as described in United State Patent No. 6,390,979. A pattern of blood flow velocity changes is obtained in response to a set intelligence task, which is used to form a 'mental signature' that could be repeatedly recognized, in an automated man-machine interface system. The system is designed to go beyond passive recognition, but rather to set a desired level of 'mental performance', before access is gained into the system. The device could be used as a 'lie detector' based on the fact that, it could distinguish Wrong ANSWER which elicits bi-hemispheric activation, from Correct ANSWER that activates unilateral response.[citation needed]


[edit] Comparison of various biometric technologies
It is possible to understand if a human characteristic can be used for biometrics in terms of the following parameters:

[21]

Universality
each person should have the characteristic
Uniqueness
is how well the biometric separates individually from another.
Permanence
measures how well a biometric resists aging.
Collectability
ease of acquisition for measurement.
Performance
accuracy, speed, and robustness of technology used.
Acceptability
degree of approval of a technology.
Circumvention
ease of use of a substitute.
The following table shows a comparison of existing biometric systems in terms of those parameters:

Comparison of various biometric technologies, modified from Jain et al., 2004[21] (H=High, M=Medium, L=Low) Biometrics: Universality Uniqueness Permanence Collectability Performance Acceptability Circumvention*
Face H L M H L H L
Fingerprint M H H M H M H
Hand geometry M M M H M M M
Keystrokes L L L M L M M
Hand veins M M M M M M H
Iris H H H M H L H
Retinal scan H H M L H L H
Signature L L L H L H L
Voice M L L M L H L
Facial thermograph H H L H M H H
Odor H H H L L M L
DNA H H H L H L L
Gait M L L H L H M
Ear Canal M M H M M H M

A. K. Jain ranks each biometric based on the categories as being either low, medium, or high. A low ranking indicates poor performance in the evaluation criterion whereas a high ranking indicates a very good performance.


[edit] Biometric systems

The basic block diagram of a biometric systemThe diagram on right shows a simple block diagram of a biometric system. When such a system is networked together with telecommunications technology, biometric systems become telebiometric systems. The main operations a system can perform are enrollment and test. During the enrollment, biometric information from an individual is stored. During the test, biometric information is detected and compared with the stored information. Note that it is crucial that storage and retrieval of such systems themselves be secure if the biometric system is to be robust. The first block (sensor) is the interface between the real world and our system; it has to acquire all the necessary data. Most of the times it is an image acquisition system, but it can change according to the characteristics desired. The second block performs all the necessary pre-processing: it has to remove artifacts from the sensor, to enhance the input (e.g. removing background noise), to use some kind of normalization, etc. In the third block features needed are extracted. This step is an important step as the correct features need to be extracted and the optimal way. A vector of numbers or an image with particular properties is used to create a template. A template is a synthesis of all the characteristics extracted from the source, in the optimal size to allow for adequate identifiability.

If enrollment is being performed the template is simply stored somewhere (on a card or within a database or both). If a matching phase is being performed, the obtained template is passed to a matcher that compares it with other existing templates, estimating the distance between them using any algorithm (e.g. Hamming distance). The matching program will analyze the template with the input. This will then be output for any specified use or purpose (e.g. entrance in a restricted area ) .


[edit] Functions
A biometric system can provide the following two functions [22]:

Verification
Authenticates its users in conjunction with a smart card, username or ID number. The biometric template captured is compared with that stored against the registered user either on a smart card or database for verification.
Identification
Authenticates its users from the biometric characteristic alone without the use of smart cards, usernames or ID numbers. The biometric template is compared to all records within the database and a closest match score is returned. The closest match within the allowed threshold is deemed the individual and authenticated.

[edit] Performance
Biometric systems are succeptable to the following kinds of errors:

False Rejection Rate (FRR) or Type I Error
False Acceptance Rate (FAR) or Type II Error
[23]

Performance measurement Measurement Shorthand acronym Description
false accept rate or false match rate FAR or FMR the probability that the system incorrectly declares a successful match between the input pattern and a non-matching pattern in the database. It measures the percent of invalid matches. These systems are critical since they are commonly used to forbid certain actions by disallowed people.
false reject rate or false non-match rate FRR or FNMR the probability that the system incorrectly declares failure of match between the input pattern and the matching template in the database. It measures the percent of valid inputs being rejected.
receiver operating characteristic or relative operating characteristic ROC In general, the matching algorithm performs a decision using some parameters (e.g. a threshold). In biometric systems the FAR and FRR can typically be traded off against each other by changing those parameters. The ROC plot is obtained by graphing the values of FAR and FRR, changing the variables implicitly. A common variation is the Detection error trade-off (DET), which is obtained using normal deviate scales on both axes. This more linear graph illuminates the differences for higher performances (rarer errors).
equal error rate or crossover error rate EER or CER the rate at which both accept and reject errors are equal. ROC or DET plotting is used because how FAR and FRR can be changed, is shown clearly. When quick comparison of two systems is required, the EER is commonly used. Obtained from the ROC plot by taking the point where FAR and FRR have the same value. The lower the EER, the more accurate the system is considered to be.
failure to enroll rate FTE or FER the percentage of data input is considered invalid and fails to input into the system. Failure to enroll happens when the data obtained by the sensor are considered invalid or of poor quality.
failure to capture rate FTC Within automatic systems, the probability that the system fails to detect a biometric characteristic when presented correctly.
template capacity the maximum number of sets of data which can be input into the system..

As the sensitivity of biometric devices increases, it decreases the FAR but increases the FRR.

The following table shows the state of art of some biometric systems:




State of art of biometric recognition systems Biometrics EER FAR FRR Subjects Comment Reference
Face n.a. 1% 10% 37437 Varied lighting, indoor/outdoor FRVT (2002)[24]
Fingerprint n.a. 1% 0.1% 25000 US Government operational data FpVTE (2003)[25]
Fingerprint 2% 2% 2% 100 Rotation and exaggerated skin distortion FVC (2004)[26]
Hand geometry 1% 2% 0.1% 129 With rings and improper placement (2005)[27]
Iris < 1% 0.94% 0.99% 1224 Indoor environment ITIRT (2005)[28]
Iris 0.01% 0.0001% 0.2% 132 Best conditions NIST (2005)[29]
Keystrokes 1.8% 7% 0.1% 15 During 6 months period (2005)[30]
Voice 6% 2% 10% 310 Text independent, multilingual NIST (2004)[31]

One simple but artificial way to judge a system is by EER, but not all the authors provided it. Moreover, there are two particular values of FAR and FRR to show how one parameter can change depending on the other. For fingerprint there are two different results, the one from 2003 is older but it was performed on a huge set of people, while in 2004 far fewer people were involved but stricter conditions have been applied. For iris, both references belong to the same year, but one was performed on more people, the other one is the result of a competition between several universities so, even if the sample is much smaller, it could reflect better the state of art of the field.
As with many interesting and powerful developments of technology, there are concerns about biometrics. The biggest concern is the fact that once a fingerprint or other biometric source has been compromised it is compromised for life, because users can never change their fingerprints. A theoretical example is a debit card with a personal Identification Number (PIN) or a biometric. Some argue that if a person's biometric data is stolen it might allow someone else to access personal information or financial accounts, in which case the damage could be irreversible. However, this argument ignores a key operational factor intrinsic to all biometrics-based security solutions: biometric solutions are based on matching, at the point of transaction, the information obtained by the scan of a "live" biometric sample to a pre-stored, static "match template" created when the user originally enrolled in the security system. Most of the commercially available biometric systems address the issues of ensuring that the static enrollment sample has not been tampered with. More importantly, one can prevent that malicous verifiers can steal templates from the database, see private biometrics [32].

So the problem can effectively be limited to cases where the scanned "live" biometric data is hacked. Even then, most competently designed solutions contain anti-hacking routines. For example, the scanned "live" image is virtually never the same from scan to scan owing to the inherent plasticity of biometrics; so, ironically, a "replay" attack using the stored biometric is easily detected because it is too perfect a match.

The television program MythBusters attempted to break into a commercial security door equipped with biometric authentication as well as a personal laptop so equipped.[33] While the laptop's system proved more difficult to bypass, the advanced commercial security door with "live" sensing was fooled with a printed scan of a fingerprint after it had been licked. There is no basis to assume that the tested security door is representative of the current typical state of biometric authentication, however. With careful matching of tested biometric technologies to the particular use that is intended, biometrics provide a strong form of authentication that effectively serves a wide range of commercial and government applications.

Biometric verification of an individual’s identity can help control the risks associated with misidentification. However, biometric verification can itself be compromised through vulnerabilities in the system. This can occur through deliberate attempts to breach security and the integrity of the biometric process as shown in the television program MythBusters. To address this risk the Biometrics Institute has established a Biometrics Vulnerability Assessment Methodology.

However, the clear concern is that the number of biometric samples of an individual are limited. If all samples are lost via compromise the legitimate owner will be unable to replace the old ones. Additionally, the limited number of samples means that there is a concern with secondary use of biometric data: a user who accesses two systems with the same fingerprint may allow one to masquerade is her to the other. Several solutions to this problem are actively being researched.[citation needed]


[edit] Privacy
A concern is how a person's biometric, once collected, can be protected. Australia has therefore introduced a Biometrics Institute Privacy Code in order to protect consumer personal data beyond the current protections offered by the Australian Privacy Act.

Another concern is that if the system is used at more than one location, a person's movements may be tracked as with any non-anonymous authentication system. An example of this would be posted security cameras linked to a facial recognition system, or a public transportation system requiring the use of biometry or registered identification card.


[edit] Biometrics sensors' obstacles
Different sensors (hardware producers), generating different biometrics outcomes, different outcomes cannot be encryptedly compared (they will never match). It is very difficult to create standard on identical encryption paths. Biometrics standard can be obtained only if the common information is unconcealed. Currently each biometric scanner's vendor is responsible for generating his own encryption method. In order to unify the biometrics collection method(s) the Standardization procedure must force Biometrics exposure, however, exposed biometrics information present a serious threat to privacy rights.


[edit] Marketing of biometric products
Despite confirmed cases of defeating commercially available biometric scanners, many companies marketing biometric products (especially consumer-level products such as readers built into keyboards) claim the products as replacements, rather than supplements, for passwords. Furthermore, regulations regarding advertising and manufacturing of biometric products are (as of 2006) largely non-existent. Consumers and other end users must rely on published test data and other research that demonstrate which products meet certain performance standards and which are likely to work best under operational conditions. Given the ease with which other security measures such passwords and access tokens may be compromised, and the relative resistance of biometrics to being defeated through alteration and reverse engineering, large scale adoption of biometrics may offer significant protection against the economic and social problems associated with identity theft.[citation needed]

The use of fingerprints for identification in schools

[edit] Sociological concerns
As technology advances, and time goes on, more private companies and public utilities may use biometrics for safe, accurate identification. These advances are likely to raise concerns such as:

Physical
Some believe this technology can cause physical harm to an individual using the methods, or that instruments used are unsanitary. For example, there are concerns that retina scanners might not always be clean.
Personal Information
There are concerns whether our personal information taken through biometric methods can be misused, e.g. by the government to determine unwanted traits in humans for global population control. Also, the data obtained using biometrics can be used in unauthorized ways without the individual's consent.

[edit] Danger to owners of secured items
When thieves cannot get access to secure properties, there is a chance that the thieves will stalk and assault the property owner to gain access. If the item is secured with a biometric device, the damage to the owner could be irreversible, and potentially cost more than the secured property. For example, in 2005, Malaysian car thieves cut off the finger of a Mercedes-Benz S-Class owner when attempting to steal the car[34].


[edit] Cancelable Biometrics
Physical features, such as face, fingerprint, iris, retina, hand, or behavioral features, such as signature, voice, gait, must fulfill a certain criteria to qualify for use in recognition. They must be unique, universal, acceptable, collectible and convenient to the person, in addition, to reliability at recognition, performance and circumvention. Most importantly, however, permanence is a key feature for biometrics. They must retain all the above features in particular the uniqueness unchanged, or acceptably changed, over the lifetime of the individual. On the other hand, this fundamental feature has brought biometrics to challenge a new risk. If biometric data is obtained, for example compromised from a database, by unauthorized users, the genuine owner will lose control over them forever and lose his/her identity.

Previously, research was focusing on using biometrics to overcome the weakness in traditional authentication systems that use tokens, passwords or both. Weakness, such as sharing passwords, losing tokens, guessable passwords, forgetting passwords and a lot more, were successfully targeted by biometric systems, although accuracy still remains a great challenge for many different biometric data. But one ordinary advantage of password does not exist in biometrics. That is re-issue. If a token or a password is lost or stolen, they can be cancelled and replaced by a newer version i.e. reissued. On the other hand, this is not naturally available in biometrics. If someone’s face is compromised from a database, they cannot cancel it neither reissue it. All data, including biometrics is vulnerable whether in storage or in processing state. It is relatively recently research has been undertaken to consider protection of biometric data more seriously. Cancelable biometrics is a way in which to inherit the protection and the replacement features into biometrics. It was first proposed by Ratha et al.[35]. Besides reliable accuracy performance and the replacement policy cancellable biometric has to be non-revisable in order to fulfill the aim.

Several methods for generating cancellable biometrics have been proposed. Essentially, cancelable biometrics perform a distortion of the biometric image or features before matching. The variability in the distortion parameters provides the cancelable nature of the scheme. Some of the proposed techniques operate using their own recognition engines, such as Teoh et al.[36] and Savvides et al.[37], whereas other methods, such as Dabbah et al.[38], take the advantage of the advancement of the well-established biometric research for their recognition front-end to conduct recognition. Although this increases the restrictions on the protection system, it makes the cancellable templates more accessible for available biometric technologies.

In general, cancelable biometrics may be seen to represent a promising approach to address biometric security and privacy vulnerabilities. However, there are several concerns about the security of such schemes. First, there is very little work analysing their security, except for an analysis of biohashing [39]. Secondly, while distortion schemes should be preferably non-invertible[40], no detailed proposed scheme has this property. In fact, it would appear to be trivial to undistort the template given knowledge of the distortion key in most cases. Third, cancelable biometrics would appear to be difficult to implement in the untrusted scenarios for which they are proposed: if the user does not trust the owner of the biometric sensor to keep the biometric private, how can they enforce privacy on the distortion parameters used? This last concern is perhaps the most serious: the security of cancelable biometrics depends on secure management of the distortion parameters, which must be used for enrollment and made available at matching. Furthermore, such keys may not be much better protected than current passwords and PINs. In summary, cancelable biometrics offer a possible solution to certain serious security and privacy concerns of biometric technology; however, current schemes leave a number of important issues unaddressed. Research is very active in this subject, and may succeed in addressing these concerns.


[edit] Uses and initiatives

[edit] Australia
Visitors intending to visit Australia may soon have to submit to biometric authentication as part of the Smartgate system, linking individuals to their visas and passports. Biometric data are already collected from some visa applicants by Immigration. Australia is the first country to introduce a Biometrics Privacy Code, which is established and administered by the Biometrics Institute. The Biometrics Institute Privacy Code Biometrics Institute forms part of Australian privacy legislation. The Code includes privacy standards that are at least equivalent to the Australian National Privacy Principles (NPPs) in the Privacy Act and also incorporates higher standards of privacy protection in relation to certain acts and practices. Only members of the Biometrics Institute are eligible to subscribe to this Code. Biometrics Institute membership, and thus subscription to this Code, is voluntary.


[edit] Brazil
Since the beginning of the 20th century, Brazilian citizens have had user ID cards. The decision by the Brazilian government to adopt fingerprint-based biometrics was spearheaded by Dr. Felix Pacheco at Rio de Janeiro, at that time capital of the Federative Republic. Dr. Pacheco was a friend of Dr. Juan Vucetich, who invented one of the most complete tenprint classification systems in existence. The Vucetich system was adopted not only in Brazil, but also by most of the other South American countries. The oldest and most traditional ID Institute in Brazil (Instituto de Identificação Félix Pacheco) was integrated at DETRAN [9] (Brazilian equivalent to DMV) into the civil and criminal AFIS system in 1999.

Each state in Brazil is allowed to print its own ID card, but the layout and data are the same for all of them. The ID cards printed in Rio de Janeiro are fully digitized using a 2D bar code with information which can be matched against its owner off-line. The 2D bar code encodes a color photo, a signature, two fingerprints, and other citizen data. This technology was developed in 2000 in order to enhance the safety of the Brazilian ID cards.

By the end of 2005, the Brazilian government started the development of its new passport. The new documents started to be released by the beginning of 2007, at Brasilia-DC. The new passport included several security features, like Laser perforation, UV hidden symbols, security layer over variable data and etc.. Brazilian citizens will have their signature, photo, and 10 rolled fingerprints collected during passport requests. All of the data is planned to be stored in ICAO E-passport standard. This allows for contactless electronic reading of the passport content and Citizens ID verification since fingerprint templates and token facial images will be available for automatic recognition.


[edit] Germany
The biometrics market in Germany will experience enormous growth until 2009. “The market size will increase from approximately 12 million € (2004) to 377 million €” (2009). “The federal government will be a major contributor to this development”.[41] In particular, the biometric procedures of fingerprint and facial recognition can profit from the government project.[41] In May 2005 the German Upper House of Parliament approved the implementation of the ePass, a passport issued to all German citizens which contain biometric technology. The ePass has been in circulation since November 2005, and contains a chip that holds a digital photograph and one fingerprint from each hand, usually of the index fingers, though others may be used if these fingers are missing or have extremely distorted prints. “A third biometric identifier – iris scans – could be added at a later stage”.[42] An increase in the prevalence of biometric technology in Germany is an effort to not only keep citizens safe within German borders but also to comply with the current US deadline for visa-waiver countries to introduce biometric passports.[42] In addition to producing biometric passports for German citizens, the German government has put in place new requirements for visitors to apply for visas within the country. “Only applicants for long-term visas, which allow more than three months' residence, will be affected by the planned biometric registration program. The new work visas will also include fingerprinting, iris scanning, and digital photos”.[43]

Germany is also one of the first countries to implement biometric technology at the Olympic Games to protect German athletes. “The Olympic Games is always a diplomatically tense affair and previous events have been rocked by terrorist attacks - most notably when Germany last held the Games in Munich in 1972 and 11 Israeli athletes were killed”.[44]

Biometric technology was first used at the Olympic Summer Games in Athens, Greece in 2004. “On registering with the scheme, accredited visitors will receive an ID card containing their fingerprint biometrics data that will enable them to access the 'German House'. Accredited visitors will include athletes, coaching staff, team management and members of the media”.[44]

As a protest against the increasing use of biometric data, the influential hacker group Chaos Computer Club published a fingerprint of German Minister of the Interior Wolfgang Schäuble in the March 2008 edition of its magazine Datenschleuder. The magazine also included the fingerprint on a film that readers could use to fool fingerprint readers.[45]


[edit] Iraq
Biometrics are being used extensively in Iraq to catalogue as many Iraqis as possible providing Iraqis with a verifiable identification card, immune to forgery. During account creation, the collected biometrics information is logged into a central database which then allows a user profile to be created. Even if an Iraqi has lost their ID card, their identification can be found and verified by using their unique biometric information. Additional information can also be added to each account record, such as individual personal history. This can help American forces determine whether someone has been causing trouble in the past. One major system in use in Iraq is called BISA.[46] This system uses a smartcard and a user's biometrics (fingerpint, iris, and face photos) to ensure they are authorized access to a base or facility.[47] Another is called BAT for Biometric Automated Toolset.[48]


[edit] Japan
Several banks in Japan have adopted either palm vein authentication or finger vein authentication technology on their ATMs. Palm vein authentication technology which was developed by Fujitsu, among other companies, proved to have a false acceptance rate of 0.01177% and a false rejection rate of 4.23%. Finger vein authentication technology, developed by Hitachi, has a false acceptance rate of 0.0100% and a false rejection rate of 1.26%. [49] Finger vein authentication technology has so far been adopted by banks such as Sumitomo Mitsui Financial Group, Mizuho Financial Group and Japan Post Bank. Palm vein authentication technology has been adopted by banks such as the Bank of Tokyo-Mitsubishi UFJ. [50]


[edit] Nigeria
The Nigerian Government has now rolled out fingerprint recognition throughout its airports on flights to reduce passport fraud. All new passports distributed now have a biometric chip containing the individuals characteristic in encrypted template form.[citation needed]


[edit] United Kingdom
Fingerprint scanners used in some schools to facilitate the subtraction of funds from an account financed by parents for the payment of school dinners. By using such a system nutritional reports can be produced for parents to surveil a child's intake. This has raised questions from liberty groups as taking away the liberty of choice from the youth of society. Other concerns arise from the possibility of data leaking from the providers of school meals to interest groups that provide health services such as the NHS and insurance groups that may end up having a detrimental effect on the ability of individuals to enjoy equality of access to services.


[edit] United States
The United States government has become a strong advocate of biometrics with the increase in security concerns in recent years, since September 11, 2001. Starting in 2005, US passports with facial (image-based) biometric data were scheduled to be produced. Privacy activists in many countries have criticized the technology's use for the potential harm to civil liberties, privacy, and the risk of identity theft. Currently, there is some apprehension in the United States (and the European Union) that the information can be "skimmed" and identify people's citizenship remotely for criminal intent, such as kidnapping. There also are technical difficulties currently delaying biometric integration into passports in the United States, the United Kingdom, and the rest of the EU. These difficulties include compatibility of reading devices, information formatting, and nature of content (e.g. the US currently expect to use only image data, whereas the EU intends to use fingerprint and image data in their passport RFID biometric chip(s)).

The speech made by President Bush on May 15, 2006, live from the Oval Office, was very clear: from now on, anyone willing to go legally in the United States in order to work there will be card-indexed and will have to communicate his fingerprints while entering the country.

"A key part of that system [for verifying documents and work eligibility of aliens] should be a new identification card for every legal foreign worker. This card should use biometric technology,such as digital fingerprints, to make it tamper-proof." President George W Bush (Addresses on Immigration Reform, May 15, 2006). Bush issued a presidential directive (NSPD 59, HSPD 24)[51] in 2008 which requires increased capability for sharing and interoperability in "collection, storage, use, analysis, and sharing of biometric and associated biographic and contextual information of individuals" among the departments and agencies of the executive branch of the U.S. federal government.[51][52]

The US Department of Defense (DoD) Common Access Card, is an ID card issued to all US Service personnel and contractors on US Military sites. This card contains biometric data and digitized photographs. It also has laser-etched photographs and holograms to add security and reduce the risk of falsification. There have been over 10 million of these cards issued.

According to Jim Wayman, director of the National Biometric Test Center at San Jose State University, Walt Disney World is the nation's largest single commercial application of biometrics.[53] However, the US Visit program will very soon surpass Walt Disney World for biometrics deployment.

On February 6, 2008, West Virginia University, in Morgantown, West Virginia, became the national academic leader for the FBI's biometric research.[54] [55] The university was the first in the world to establish a Bachelor of Science Degree in Biometric Systems, and also established the initial chapter of the Student Society for the Advancement of Biometrics (SSAB) in 2003.[56] WVU also offers a graduate level certificate and Master’s degree emphasis in Biometrics.


[edit] Venezuela
In the year 2004 Venezuela's National Elections Counsel, or (CNE), adopted a fingerprint validation system which is used to avoid double voting in regular elections; used since then the investment was made to allow the sending of voters template information at real time with and then verify it before accessing the secret voting ballot room. Voting population is approximately estimated for 2008 at 17 million voters, in the last years more than 11 election had been realized and the verification system is operated in most of the voting locations.