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Biometric authentication is an automated method
whereby an individual's identity is confirmed by
examining a unique physiological trait or behavioral
characteristic, such as a fingerprint, iris, or
signature. Physiological traits are stable physical
characteristics, such as palm prints and iris
patterns. A behavioral characteristic-such as one's
signature, voice, or keystroke dynamics-is
influenced by both controllable actions and less
controllable psychological factors. Although
behavior-based biometrics can be less expensive and
less threatening to users, physiological traits tend
to offer greater accuracy and security. In any case,
both techniques provide a significantly higher level
of identification than passwords or smart cards
alone.
The accuracy and
performance of biometric based system is measured by
the following four criteria: FRR (False Rejection
Rate), FAR (False Acceptance Rate), FER (Failure to
Enroll Rate), and ERR (Equal Error Rate). Learn more
about these values and their significance in the
selection process section, where we discuss the
different criteria determining the selection of the
'perfect' authentication technology.
All biometric
systems operate in a similar fashion. First, the
system captures a sample of the biometric
characteristic during the enrollment process. Unique
features are then extracted and converted by the
system into a mathematical code. This sample is then
stored as the biometric template for the enrollee.
The following
four-stage process illustrates the way in which
biometric systems generally operate:
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Capture - a physical or behavioral
sample is captured during enrollment |
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Extraction - unique data is extracted
from the sample and a template is created |
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Comparison/Match - the template is
compared with a new sample and the system
determines whether there is a match. |
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Storage - the system stores template
data only on the server, workstation, etc. |
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At the heart of the biometric system is the
biometric engine, a proprietary element that
extracts and processes the biometric data. The
system may apply an algorithm or an artificial
neural network. |
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