GUIDE TO BIOMETRICS

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GUIDE TO BIOMETRICS CHAPTER I II September
7th 2005 Presentation by Tamer Uz
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Chapter IIntroduction
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Outline

• Descriptions
• Authentication
• Overview of Biometric Systems
• Biometric Identification
• Biometric Verification
• Biometric Enrollment
• Biometric System Security

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Descriptions

• Biometrics Science of identifying, or verifying
  the identity of, a person based on physiological
  or behavioral characteristics.

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Descriptions

• Authentication Validating or figuring out the
  identity of a person.

• Authorization Permission or approval.

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Authentication

• There are 3 traditional way of verifying the
  identity of a person
• Possessions (keys, passports, smartcards , )
• Knowledge
• Secret (passwords, pass phrases, )
• Non-secret (user Id, mothers maiden name,
  favorite color)
• Biometrics
• Physiological (fingerprints, face, iris, )
• Behavioral (walking, keystroke pattern, talking,
  )

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Authentication

• The 3 modes of authentication are sometimes
  combined
• User id password
• ATM card password
• Passport face picture and signiture

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Authentication

• There are two different authentication methods in
  biometrics
• Verification Is he/she the person who claims
  he/she is? Works with id biometrics. Thus it is
  based on a combination of modes.
• Identification Who is this person? Uses only the
  biometrics and searches the entire database.

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Overview of Biometric Systems

• There are five important properties of biometric
  identifiers
• 1. Universality
• 2. Uniqueness
• 3. Permanence
• 4. Collectability
• 5. Acceptability

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Overview of Biometric Systems

• Biometric Identifiers

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Overview of Biometric Systems

• Biometric Subsystems
• Biometric readers (sensors)
• Feature extractors
• Feature Matchers

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Overview of Biometric Systems

• A generalized diagram of a biometric system is as
  follows

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Overview of Biometric Systems

• Design Issues
• 4 basic design specifications of biometric
  systems are
• System accuracy
• How often the system accepts an imposter (FAR)
• How often the system rejects a genuine user (FRR)
• Computational Speed
• Exception Handling
• Failure to use (FTU)
• Failure to enroll (FTE)
• Failure to acquire (FTA)
• System Cost

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Overview of Biometric Systems

• What feature set is amenable for automatic
  matching?
• Given the input data how to extract the features
  from it?
• How to define a matching metric that translates
  the intuition of similarity among the patterns?
• How to implement the matching metric?
• Organization of the database?
• Methods for searching the database?
• Security?
• Privacy?

• Engineering Questions
• Trusting people/biometrics?
• Which biometrics is best for a given application?
• How are the error numbers that are reported for
  different biometrics to be interpreted?
• Are new security holes created because of the use
  of the biometrics?
• How to achieve a low exception rate?
• How to acquire the biometrics and how to do it in
  a convenient way?

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Biometric Identification

• Biometric identification is based only on
  biometric credentials.

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Biometric Identification

• Biometric identification system can be used in
  two different modes
• Positive identification
• Authorization of a group without id
• Negative identification
• Most Wanted List

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Biometric Verification

• Biometric verification differs from biometric
  identification in that the presented biometric is
  only compared with a single enrolled biometric
  entity which matches the input id

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Biometric Verification

• There are two possible database configurations
  for the verification systems
• Centralized Database As the name suggests the
  enrollment information is in a central database.
  When the token (id/card) is provided, the
  corresponding biometrics is retrieved and the
  comparison is made with the newly presented
  biometric sample. E.g. laptop
• Distributed Database In this case the enrollment
  template is usually stored in a device that the
  user carries. The user provides the device and
  his/her biometrics. Then the comparison is
  performed between the two. E.g. smart cards

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Biometric Enrollment

• Process of registering subjects in biometric
  database
• Positive Enrollment
• To create a database of eligible subjects
• Biometric samples and other credentials are
  stored in the database. An id (or a smart card)
  is issued to the subject.
• Negative Enrollment
• To create a database of ineligible subjects
• Often without subject cooperation or even
  knowledge

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Biometric System Security

• Possible Security Concerns
• Biometric information is presented when the owner
  is not present.
• Hacking the scanner, feature extractor, matcher,
  database, and any other possible module in the
  system.

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Chapter IIAuthenticationandBiometrics
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Outline

• Descriptions
• Secure Authentication Protocols
• Access Control Security Services
• Authentication Methods
• Authentication Protocols
• Matching Biometric Samples
• Verification by Humans
• Passwords vs. Biometrics
• Hybrid Methods

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Descriptions

• Authorization Permission to access a resource
• Access Control A mechanism for limiting the use
  of some resource to authorized users
• Access Control List A data structure associated
  with a resource that specifies the authorized
  users and the conditions for their access
• Authenticate To determine that something is
  genuine to determine reliably the identity of
  the communicating party
• Authentication Permission to access a resource

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Secure Authentication Protocols

• Characteristics of an authentication protocol
• Established in advance
• Mutually agreed
• Unambiguous
• Complete (Able to handle exceptions)
• An authentication protocol itself does not
  guarantee security

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Access Control Security Services

• Some basic security services that should be
  offered by any access control system are
• Authentication
• Non-repudiation
• Confidentiality

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Authentication Methods

• Possession (P)
• Knowledge (K)
• Biometrics (B)

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Authentication Protocols

• Authentication protocol is the tasks the user and
  the access point has to perform to be able to
  determine whether the user has enough credentials
  or not.
• Part of Authentication Protocols
• Enrollment
• Tokens. E.g. Tx1xnxi ? (P,K,B)
• Comparison rules. E.g. Matching threshold
• Other rules. E.g. Three strikes and you are
  out, or the order of the presentation of the
  tokens First id number, then the fingerprint,
  and than the key

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Matching Biometric Samples

• Remark
• P and K are checked by exact comparison
• B is compared via pattern recognition techniques
  because of sampling variations, noise and
  distortions

• Three crucial design aspects of biometric system
• The biometric sampling or signal acquisition
  (Bf(ß))
• The similarity function ss(B1, B2) between two
  templates
• The decision threshold T that decides on a match
  or mismatch

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Matching Biometric Samples

• Identification
• Only the biometrics is needed (no id is claimed).

• Authorization is granted if ddi
• Multiple di might satisfy the similarity
  criteria. A secondary matcher (possible a human
  expert) tries to narrow it down.

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Matching Biometric Samples

• Screening
• Negative identification.
• Searching whether a subject is in an
  interesting people database or not. (Most
  wanted criminals)
• Using biometrics only may result in too many
  false positives (or false negatives depending on
  T). Bad ROC.
• Therefore several tokens P1, B1, K1, P2, K2, B2
  etc. should be matched with the ones in the file.

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Matching Biometric Samples

• Verification
• Id B is provided. (Sometimes K too)
• The template corresponding the Id is retrieved
  from the database
• If s(B,Bi)gtT pass, else fail.

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Matching Biometric Samples

• Continuity of Identity
• Are the authenticated and authorized persons the
  same?
• Re-establishing the authentication credentials
• Surveillance cameras

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Verification by Humans

• By looking at the biometrics (face, signatures)
• Face verification error rate 11000
• Signature verification is not very secure

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Passwords versus Biometrics

• Passwords Exact match
• Biometrics Probabilistic match
• FAR, FRR

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Hybrid Methods

• More than one identifier is used P, K, B
• Two Remarks
• B with P, K. Reduces identification to
  verification (from 1many to 11)
• B1 with B2. Results in better ROCs than using
  only B1 or only B2
• Combination of matching scores is an application
  specific problem

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QUESTIONS?