The some of the materials are excerpted from Paul Reid, ’s Book, John Chirillo and Scott Blaul ’s Book, and Ross Anderson’s Book
WHO ARE YOU?
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HOW ARE PEOPLE IDENTIFIED?
People’s identity are verified and identified by three basic means:
Something they have (identity document or token)
Something they know (password, PIN)
Something they are (human body such as fingerprint or iris).
The strongest authentication involves a combination of all three.
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PERSON IDENTIFICATION
Identifying fellow human beings has been crucial to the fabric of human society
the early days of civilization, people lived in small communities and everyone knew each other
With the population growth and increase in mobility, we started relying on documents and secrets to establish identity
Person identification is now an integral part of the infrastructure needed for diverse business sectors such as banking, border control, law enforcement.
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AUTOMATIC IDENTIFICATION
Different means of automatic identification:
Possession-based (credit card, smart card)
“something that you have”
Knowledge-based (password, PIN)
“something that you know”
Biometrics-based (biometric identifier)
“something about or produced by your physical make-up”
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PROBLEMS WITH POSSESSION- OR KNOWLEDGE-BASED APPROACHES
Card may be lost, stolen or forgotten
Password or PIN may be forgotten or guessed by the imposters
of people seem to write their PIN on their ATM card
Estimates of annual identity fraud damages:
billion in credit card transactions in U.S. alone in 2005*
f internet transactions revenues, 0.08% of off-line revenues
billion in fraudulent cellular phone use
billion in ATM withdrawals
The traditional approaches are unable to differentiate between an authorized person and an impostor
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IDENTIFICATION PROBLEMS
Identity Theft: Identity thieves steal PIN (e.g., date of birth) to open credit card accounts, withdraw money from accounts and take out loans
3 million identity thefts in U.S. in 2010; 6.7 million victims of credit card fraud
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Surrogate representations of identity such as passwords and ID cards no longer suffice
WHAT ARE BIOMETRICS?
Biometrics – science, which deals with the automated recognition of individuals (or plants/animals) based on biological and behavioral characteristics
Biometry – mathematical and statistical analysis of biological data
Biometric system – a pattern recognition system that recognizes a person by determining the authenticity of a specific biological and/or behavioral characteristic (biometric)
Anthropometry–measurement techniques of human body and its specific parts
Forensic (judicial) anthropometry–identification of criminals by these measurement techniques
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WHY BIOMETRICS?
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MENTIONING THE OBVIOUS
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REQUIREMENTS FOR AN IDEAL BIOMETRIC IDENTIFIER
Universality
– Every person should have the biometric characteristic
Uniqueness
two persons should be the same in terms of the biometric characteristic
Performance
The biometric characteristic should be invariant over time
Collectability
The biometric characteristic should be measurable with some (practical) sensing device
Acceptability
One would want to minimize the objections of the users to the measuring/collection of the biometric
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IDENTIFIABLE BIOMETRIC CHARACTERISTICS
Biological traces
DNA (DeoxyriboNucleic Acid), blood, saliva,etc.
Biological (physiological) characteristics
fingerprints, eye irises and retinas, hand palms and geometry, and facial geometry
Bertillon system (1882) took a subject's photograph, and recorded height, the length of one foot, an arm and index finger
Galton/Henry system of fingerprint classification adopted by Scotland Yard in 1900
FBI set up a fingerprint identification division in 1924
AFIS installed in 1965 with a database of 810,000 fingerprints
First face recognition paper published in 1971 (Goldstein et al.)
FBI installed IAFIS in ~2000 with a database of 47 million 10 prints; average of 50,000 searches per day; ~15% of searches are in lights out mode; 2 hour response time for criminal search
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Emphasis now is to automatically perform reliable person
identification in unattended mode, often remotely (or at a distance)
Biometrics
biometric authentication system uses the physiological (fingerprints, face, hand geometry, iris) and/or behavioral traits (voice, signature, keystroke dynamics) of an individual to identify a person or to verify a claimed identity.
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COMPARISON OF BIOMETRIC TECHNIQUES
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Biometrics is the automated use of physiological or behavioral characteristics to determine or verify identity.
Automated use means using computers or machines, rather than human beings, to verify or determine physiological or behavioral characteristics.
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Categories of Biometrics
Physiological – also known as static biometrics: Biometrics based on data derived from the measurement of a part of a person’s anatomy. For example, fingerprints and iris patterns, as well as facial features, hand geometry and retinal blood vessels
Behavioral – biometrics based on data derived from measurement of an action performed by a person, and distinctively incorporating time as a metric, that is, the measured action. For example, voice (speaker verification)
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Process flow includes enrollment, and verification/identification.
Enrollment
Person entered into the database
Biometric data provided by a user is converted into a template.
Templates are stored in a biometric systems for the purpose of subsequent comparison.
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Verification: Am I who I claim to be?
One to one comparison
Verification can confirm or deny the specific identification claim of a person.
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Identification: Who am I?
One to many comparison
can determine the identity of a person from a biometric database without that person first claiming an identity.
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Verification system answers the question: “Am I who I claim to be?”
The answer returned by the system is match or no match.
Identification systems answers the question: “Who am I”
The answer returned by the system is an identity such as a name or ID number.
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and Network Security -- verification
Access to buildings and rooms – either verification (predominant) or identification
Large-scale public benefit programs – identification
Verification systems are generally faster and more accurate than identification systems.
However, verification systems cannot determine whether a given person is present in a database more than once.
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Identification system requires more computational power than verification systems, and there are more opportunities for an identification system to err.
a rule, verification systems are deployed when identification simply does not make sense (to eliminate duplicate enrollment, for instance. )
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TOTAL BIOMETRICS MARKET
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DIFFERENT BIOMETRICS
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Physiological or behavioral characteristics are distinctive, which provide basic measurement of biometrics.
Physiological biometrics are based on direct measurements of a part of the human body, such as finger-scan, facial-scan, iris-scan, hand-scan, and retina-scan.
Behavioral biometrics are based on measurements and data derived from an action and therefore indirectly measure characteristics of the human body, such as voice-scan and signature-scan.
The element of time is essential to behavioral biometrics.
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DNA (DEOXYRIBO NUCLEIC ACID)THE ULTIMATE BIOMETRIC
One-dimensional unique code for one’s individuality, but identical twins have identical DNA patterns
Issues limiting the utility of DNA
Contamination
Access
Automatic real-time recognition issues
Privacy issues: information about susceptibilities of a person to certain diseases could be gained from the DNA pattern
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BEHAVIORAL VS PHYSICAL TRAITS
Physical Characteristics
Iris
Retina
Vein Pattern
Hand Geometry
Face
Fingerprint
Ear shape
Behavioral Characteristics
Keystroke dynamics
Signature dynamics
Walking Gait
Voice
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FINGERPRINTS
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FINGERPRINT FEATURES
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IRIS RECOGNITION: EYE
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NATIONAL GEOGRAPHIC 1984 AND 2002
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RETINA
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Every eye has its own totally unique pattern of blood vessels.
FACE RECOGNITION: CORRELATION
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FACE RECOGNITION: 3D
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HAND
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PALM
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VEIN
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EAR
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BIOMETRIC APPLICATIONS
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Biometric technology is used for many applications
Providing time and attendance functionality for a small company
Ensuring the integrity of a 10 million-person voter registration database
The benefit of using biometrics include increased security, increased convenience, reduced fraud or delivery of enhanced services.
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UCSD BIOMETRIC SODA MACHINE
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part of the enhanced procedures, most
visitors traveling on visas will have two
fingerprints scanned by an inkless device and a digital photograph taken. All of the data and information is then used to assist the border inspector in determining whether or not to admit the traveler. These enhanced procedures will add only seconds to the visitor’s overall processing time.
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NATIONAL BIOMETRIC ID CARDS
K. to consider national biometric ID cards,
database
Laura Rohde, COMPUTERWORLD (Nov 29, 2003)-
The U.K. government is set to consider legislation next year
for the establishment of compulsory biometric identity cards
and a central database of all U.K. subjects, it was announced
the government this week.
The information that the government is considering for
inclusion on the card includes personal details such as a
person's home address and telephone number, his National
Insurance number (the equivalent of the U.S. Social Security
number), medical information and criminal convictions, as
well as the biometric information, most likely in the form of
iris, fingerprint or palm print scan.
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ACCESS CONTROL
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DID YOU VOTE?
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APPLICATIONS
Video Surveillance (On-line or off-line)
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FINGERPRINT SYSTEM AT GAS STATIONS
“Galp Energia SGPS SA of Lisbon
won the technology innovation
award for developing a payment
system in which gasoline-station
customers can settle their bills
simply by pressing a thumb against
glass pad. Scanning technology
identifies the thumbprint and sends
the customer's identification
information into Galp's back-office
system for payment authorization.”
THE WALL STREET JOURNAL, November 15, 2004
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USING IRIS SCANS TO UNLOCK HOTEL ROOMS
The Nine Zero hotel in Boston just installed a new
system which uses digital photos of the irises of
employees, vendors and VIP guests to admit them to
certain areas, the same system used in high-security
areas at airports such as New York's JFK.
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FINGERPRINT SYSTEM AT BORDER CROSSINGS
“Foreigners entering the United
State in three cities, including
Port Huron, were fingerprinted,
photographed and subjected to
background checks on Monday
a test of a program that will
eventually be extended to
every land border crossing
nationwide.”
Lansing State Journal, Nov. 16, 2004
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NEW PASSPORTS
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The new passports have an embedded
contactless (ISO 14443) “smart-card” chip that stores personal information and a biometric template. Two problems: reliability and privacy
WANT TO CHARGE IT? YOU'LL HAVE TO TALK TO YOUR CREDIT CARD
Beepcard, a company in California, has designed a credit card that works only when it recognizes the voice of its rightful owner. Enclosed in the card is a tiny microphone, a loudspeaker and a speech recognition chip that compares the spoken password with a recorded sample. If the voices match, the card emits a set of beeps that authorize a transaction over the telephone or the Internet. If the voices do not match, the card will not beep.
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The system tolerates some variations in voice to accommodate cold or background noise. But it might not work if there is a blaring music in the background.
BIOMETRICS FOR PERSONALIZATION
Automatic personalization of vehicle settings:
Seat position
Steering wheel position
Mirror positions
Lighting
Radio station preferences
Climate control settings
URLs at your fingertips
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DOMAINS OF APPLICATION
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template is a small file derived from the distinctive features of a user’s biometric data, used to perform biometric matches.
Templates, is calculated during enrollment or verification phase. The template be understood as a compact representation of the collected feature data, where useless or redundant information is discarded.
Biometric systems store and compare biometric templates, NOT biometric data.
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Most template occupy less than 1 kilobyte, and some of them are as small as 9 bytes; size of template differs from vendor to vendor.
Templates are proprietary to each vendor and each technology, and there is no common biometric template format.
This is beneficial from a privacy perspective, but the lack of interoperability deterred some would-be users.
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Biometric data CAN NOT be reconstructed from biometric templates.
Templates are extractions of distinctive features and not adequate to reconstruct the full biometric image or data.
Unique templates are generated every time a user presents biometric data. For example, two immediately successive placement of a finger on a biometric device generate entirely different templates which are processed by vendor’s algorithm and recognizable as being from the same person,but are not identical.
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Depending on when they are generated, templates can be referred to as enrollment templates or match templates.
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Enrollment is a process to acquire, assess, process, and store user’s biometric data in the form of a template.
Stored templates are used for subsequent verification and identification.
Quality enrollment is a critical factor in the long-term accuracy of biometric system.
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Presentation is the process by which a user provides biometric data to an acquisition device – the hardware used to collect biometric data.
For example, looking in the direction of a camera, placing a finger on a platen, or reciting a passphrase.
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Biometric data are converted to templates through feature extraction.
Feature extraction is the automated process of locating and encoding distinctive characteristics from biometric data in order to generate a template.
Feature extraction removes noises and unwanted data, and digitize biometric traits.
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user may need to present biometric data several times in order to enroll.
Enrollment score or quality score indicates the enrollment attempt is successful or not.
the user’s biometric data contains highly distinctive features or an abundance of features, there will likely be a high enrollment score.
Vendor’s feature extraction processes are generally patented and are always held secret.
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Verification/Identification template is compared with enrollment templates.
The comparison renders a score, or confident value.
The score is compared with threshold.
the score exceeds the threshold, the comparison is a match, non-match otherwise.
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biometric algorithm is a recipe for turning raw data - like physical traits – into a digital representation in the form of a template. It also allows the matching of an enrolled template with a new template just created for verifying an identity, called the live template.
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Matching is the comparison of enrolled biometric templates with a new template just created for verification to determine their degree of similarity or correlation.
verification systems, a verification template is matched against a user’s enrollment template or templates (multiple).
Identification systems, the verification template is matched against dozens, thousands, even millions of enrollment templates.
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Biometric systems utilize proprietary algorithms to process templates and generate scores.
Some of them use a scale of 1 to 100, others use a scale of -1 to 1.
Traditional authentication methods such as password offer on a yes’/no response.
biometric system, there is no 100 percent correlation between enrollment and verification templates.
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threshold is a predefined number, which establishes the degree of correlation necessary for a comparison to be deemed a match.
Thresholds can vary from user to user, from transaction to transaction, and from verification to verification attempt.
System can be either highly secure for valuable transaction or less secure for low-value transaction, depending on their threshold settings.
Traditional authentication can not offer such flexibility.
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The result of the comparison between the score and the threshold is a decision.
The decisions a biometric system can make include match, non-match, and inconclusive.
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The user submits a sample (biometric data) via an acquisition device (for example, a scanner or camera)
This biometric is then processed to extract information about distinctive features to create a trial template or verification template
Templates are large number sequences. The trial/match template is the user’s “password.”
Trial/match template is compared against the reference template stored in biometric database.
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Biometric
Acquisition Device
Sample
Feature Extracted
Iris
Infrared-enabled video camera, PC camera
Black and white iris image
Furrows and striations of iris
Fingerprint
Desktop peripheral, PC card, mouse chip or reader embedded in keyboard
Fingerprint image (optical, silicon, ultrasound or touchless)
Location and direction of ridge endings and bifurcations on fingerprint, minutiae
Voice
Microphone, telephone
Voice Recording
Frequency, cadence and duration of vocal pattern
Signature
Signature Tablet, Motion-sensitive stylus
Image of Signature and record of related dynamics measurement
Speed, stroke order, pressure and appearance of signature
Face
Video Camera, PC camera, single-image camera
Facial image (optical or thermal)
Relative position and shape of nose, position of cheekbones
Hand
Proprietary Wall-mounted unit
D image of top and sides of hand
Height and width of bones and joints in hands and fingers
Retina
Proprietary desktop or wall mountable unit
Retina Image
Blood vessel patterns and retina
Biometric
Strengths
Weakness
Usability
Iris
Very stable over time
Uniqueness
Potential user resistance
Requires user training
Dependant on a single vendor’s technology
Information security access control, especially for
Federal Institutions and government agencies
Physical access control (FIs and government)
Kiosks (ATMs and airline tickets)
Fingerprint
Most mature biometric technology
Accepted reliability
Many vendors
Small template (less than 500 bytes)
Small sensors that can be built into mice, keyboards or portable devices
Physical contact required (a problem in some cultures)
Association with criminal justice
Vendor incompatibility
Hampered by temporary physical injury
access control
Physical access control
Automotive
Optical
Most proven over time
Temperature stable
Large physical size
Latent prints
CCD coating erodes with age
Durability unproven
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Biometrics
Strengths
Weakness
Usability
Silicon
Small physical size
Cost is declining
Requires careful enrollment
Unproven in sub optimal conditions
Ultrasound
Most accurate in sub optimal conditions
New technology, few implementations
Unproven long term performance
Voice
Good user acceptance
Low training
Microphone can be built into PC or mobile device
Unstable over time
Changes with time, illness stress or injury
Different microphones generate different samples
Large template unsuitable for recognition
Mobile phones
Telephone banking and other automated call centers
Signatures
High user acceptance
Minimal training
Unstable over time
Occasional erratic variability
Changes with illness, stress or injury
Enrollment takes times
Portable devices with stylus input
Applications where a “wet signature” ordinarily would be used.
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Biometrics
Strengths
Weakness
Usability
Face
Universally present
Cannot distinguish identical siblings
Religious or cultural prohibitions
Physical access control
Hand
Small template (approximately 10 bytes)
Low failure to enroll rate
Unaffected by skin condition
Physical size of acquisition device
Physical contact required
Juvenile finger growth
Hampered by temporary physical injury
Physical access control
Time and attendance
Retina
Stable over time
Uniqueness
Requires user training and cooperation
High user resistance
Slow read time
Dependent on a single vendor’s technology
access control, especially for high security government agencies
Physical access control (same as IS access control)
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False acceptance rate
False rejection rate
Failure-to-enroll rate
single metric indicates how well a biometric system or device performs: Analysis of all three metrics is necessary to assess the performance of a specific technology.
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John Smith enters Jane Doe’s username or ID, presents biometric data, and successfully matching as Jane Doe.
This is classified as false acceptance.
The probability of this happening is referred to as false acceptance rate (FAR)[ stated as: percentage, fraction]
This is because two people have similar enough biometric characteristics – a fingerprint, a voice, or a face – that the system finds a high degree of correlation between the users’ template.
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FAR can be reduced by adjusting the thresholds but the false rejection rate will increase.
system with a false acceptance rate of 0 percent, but false rejection rate of 50 percent, is secure but unusable.
False acceptance rate is the most critical accuracy metric because an imposter break-in will certainly be a more attention-getting event than other failings of a biometric system.
The most important false match metric in real-world deployments is the system false match rate.
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John Smith enters his username or ID, presents his biometric data to a biometric system, and fails to match.
This is classified as false rejection.
The probability of this happening is the false rejection rate (FRR).
This can be attributed to changes in user’s biometric data, changes in how a user presents biometric data, and changes in the environment in which data is presented.
High FRR will result in lost productivity, frustrated users, and an increased burden on help desk or support personnel.
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Changes in user’s biometric data
Voice-scan system is influenced by sore throats
Facial-scan system is affected by changes in weight
Fingerprint changes over time, scars, aging and general wear.
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someone else is trying to verify as you, the system would try to match the two templates.
the two templates were to match – this is classified as false acceptance.
your authentication template fails to match your enrolled template, then this is referred to as a false rejection.
you are new and fail to enroll to a biometric system, this is called – failure to enroll (FTE).
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Single False Acceptance Rate vs. System False Acceptance Rate
the FAR is 1/10,000 but you have 10,000 templates on file — odds of a match are very high
Ability to Verify (ATV) rate:
% of user population that can be verified
ATV = (1-FTE)(1-FRR)
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False rejection rate
True acceptance rate
Legitimate users get accepted.
Legitimate users get rejected.
Cost/benefit analysis of decision making.
Tradeoff b/w true acceptance rate and false rejection rate.
a typical IT biometric system, a person registers with the system when one or more of his physical and behavioral characteristics are obtained. This information is then processed by a numerical algorithm, and entered into a database.
The algorithm creates a digital representation of the obtained biometric – a template.
the user is new to the system, he or she enrolls, which means that the digital template of the biometric is entered into the database.
Each subsequent attempt to use the system, or authenticate, requires the biometric of the user to be captured again, and processed into a digital template. That template is then compared to those existing in the database to determine a match.
The process of converting the acquired biometric into a digital template for comparison is completed each time the user attempts to authenticate to the system.
The comparison process involves the use of a Hamming distance. This is a measurement of how similar two bit strings are.
For example, two identical bit strings have a Hamming Distance of zero, while two totally dissimilar ones have a Hamming Distance of one.
Thus, the Hamming distance measures the percentage of dissimilar bits out of the number of comparisons made.
Ideally, when a user logs in, nearly all of his/her features match;
However, if someone else tries to log in, who does not fully match, the system will not allow the new person to log in.
Current technologies have widely varying Equal Error Rates, varying from as low as 60% and as high as 99.9%.
Performance of a biometric measure is usually referred to in terms:
false accept rate (FAR)- percent of invalid users who are incorrectly accepted as genuine users,
false non match or reject rate (FRR)- percent of valid users who are rejected as impostors ,
failure to enroll rate (FTE or FER).
real-world biometric systems the FAR and FRR can typically be traded off against each other by changing some parameter.
One of the most common measures of real-world biometric systems is the rate at which both accept and reject errors are equal:
the equal error rate (EER),
also known as the cross-over error rate (CER).
The lower the EER or CER, the more accurate the system is considered to be.
EER is desirable for a biometric system because it balances the sensitivity of the system.
Excessive concern with the biometric may have the an eclipsing effect on the performance of the technology that one could:
plant DNA at the scene of the crime
associate another's identity with his biometrics, thereby impersonating without arousing suspicion
interfere with the interface between a biometric device and the host system, so that a "fail" message gets converted to a "pass".
Concerns about Identity theft through biometrics use have not been resolved. If their iris scan is stolen, though, and it allows someone else to access personal information or financial accounts, the damage could be irreversible.
Often, biometric technologies have been rolled out without adequate safeguards for personal information gathered about individuals.
Also, the biometric solution to identity theft is only as good as the information in the database that is used for verifying identity.
There are problems of getting accurate and usuable initial information (enrollment) -- witness the current troubles with the No fly list of the Dept of Homeland security.
Presumably after the initial information is correctly stored, future computer error or vandalism (hacking) would prevent biometrics from being 100% foolproof against identity theft.
Because biometrics are touted as a way to restrict criminality, privacy advocates fear biometrics may be used to diminish personal liberties of law abiding citizens as well.
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technology advances, more private companies and public utilities are using biometrics for safe, accurate identification. However, these advances are raising more concerns like:
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, tampered with, or sold, e.g. by criminals stealing, rearranging or copying the biometric data. Also, the data obtained using biometrics can be used in unauthorized ways without the individual's consent.
Society fears in using biometrics will continue over time. As the public becomes more educated on the practices, and the methods are being more widely used, these concerns will become more and more evident.
This technology is being used at border crossings that have electronic readers that are able to read the chip in the cards and verify the information present in the card and on the passport.
This method allows for the increase in efficiency and accuracy of identifying people at the border crossing. CANPASS, by Canada Customs is currently being used by some major airports that have kiosks set up to take digital pictures of a person’s eye as a means of identification.
Despite these misgivings, biometric systems have the potential to identify individuals with a very high degree of certainty.
Forensic DNA evidence enjoys a particularly high degree of public trust at present
Also substantial claims are being made in respect of iris recognition technology, which has the capacity to discriminate between individuals with identical DNA, such as monozygotic twins.
