Biometrics

Biometricsis a type of access control mechanism that can be used to verify an individual’s identity with a unique personal attribute. Examples are fingerprints,
palm scans, retina scans, and voice prints. These kinds of authentication systems
gather a lot of information that can be hard to imitate, thus they provide a
higher level of protection when compared to other authentication technologies.
Biometric systems are usually more expensive, relative to other approaches,
and do not usually have a high acceptance rate by society because they are perceived to be intrusive and they obtain personal information. Biometrics are
sometimes seen as too “Big Brother-ish” and an encroachment into our personal privacy through automated means. For these reasons, they have usually
been seen only in environments that require a very high level of security. But after what happened on September 11, 2001, they are being implemented into
more locations because of society’s increased awareness of security.
Each subject must go through an enrollment period where personal attributes are captured and then stored in a reference file. The reference file can be
held in a local or remote database or even within a biometric template of a smart
card. So, when Truman presses his finger on the reader in order to enter his
highly secure work facility, the reader references the image Truman presents
against his stored reference file. If the two match, and he supplies the correct
PIN or password, he is successfully authenticated and allowed access.
The accuracy of different biometric systems can be evaluated by two separate
measurements: Type I error and Type II error. AType I error, false reject rate, is
rejecting a subject that should be authenticated and allowed access. If Truman
is rejected when he presents his fingerprint, and he really should have been authenticated,this is referred to as a Type I error. If an imposter is successfully authenticated by the system, this is called aType II error—false accept rate. Each of these
error rates should remain low for the system to provide the necessary level of
protection and efficiency. A metric has been developed to measure different biometric systems’ overall protection and accuracy level, which is a combination of
these two error types, called the crossover error rate(CER). CER is the point at
which Type I errors (false rejection) equal Type II errors (false acceptance),
The CER can be accomplished by calibrating the system to ensure that it does
not provide more Type I errors than Type II errors and vice versa. For example,
if a system was calibrated so that it resulted in only 2 Type I errors out of 100 authentication attempts and 2 Type II errors out of 100 attempts, it would have the
CER value of 2. This system would provide a higher accuracy level than a system
that provided a CER value of 3. This metric can be used when evaluating different biometric systems for purchase.
Fingerprint Ridge endings and bifurcations on the finger.
•Finger scan Selective points on the fingerprint are collected and
stored. This uses a smaller amount of data compared to fingerprint
systems.
•Palm scan Creases and ridges on the palm and all fingerprints are
used to identify individuals.
•Hand geometry The shape of a person’s hand (length and width
of hand and fingers).
•Retina scan The patterns of the blood vessels on the backside of
the eyeball.
Iris scan The unique patterns, rings, and corona in the iris, which is
the colored portion of the eye.
•Signature dynamics Electrical signals, pressure used, slant of the pen,
the amount of time and patterns used in creating a signature are captured.
There is much more information and variables to look at when compared
to a static signature, thus harder to counterfeit.
•Keyboard dynamics Mechanism that analyzes electrical signals
when a person types a certain phrase on a keyboard, such as speed
and movement.
•Voice print This mechanism recognizes subtle differences in people’s
speech sounds and patterns.
•Facial scan Attributes of a person’s face, bone structure, nose ridges,
and eye widths.
•Hand topology Looks at a side view of a person’s hand and reviews
the height and length from that perspective.