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Biometrics

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Access to systems providing significant monetary value, confidential information, or criticalapplications must be secured against unauthorized use.

User authentication is therefore a key function in any such system. Classical authentication relieson what you own, what you are, and what you know.

Typically, Internet applications rely on user identifier (UID) and a password.

The UID may be in the public knowledge, whereas the password is a secret (what you know)shared by the user and the system administration.

Thus, the system can check whether the user is authorized to use the system.

However, any person who knows the password can perform user functions.

The password can be stolen by watching the user enter their personal identification number (PIN),by capturing data during password transmission, or via access to system administration data.

A stolen password is hard to detect because nothing is removed from any system.

GSM mobile phones are protected against unauthorized use through the SIM, a smart card that isissued by the mobile service provider (what you have) and a PIN chosen by the customer (whatyou know).

The PIN is stored and checked in the secure system environment of the SIM and is not

transmitted via unreliable media. Intruders must steal the SIM and the PIN in order to act like the authorized user and perform user

functions.

However, many users prefer not to use a PIN because it is inconvenient, and complicatedprocedures are required to recover a for gotten PIN and assign a new one

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Biometrics authentication methods rely on what you are.

A large number of personal characteristics, such as fingerprint, signature, ham geometry, facerecognition, voice recognition, and iris scan, have been proposed.

Only methods that work with small sensors, e.g. microphone fingerprint sensor, or pen entrypanels, promise near-term applicability of the pervasive computing space.

Therefore, only authentication using fingerprint, speaker verification, or signature verification isdiscussed in the following section.

Biometrics authentication systems capture the user's characteristic with a sensor, derivecharacteristic values, and compare this with known reference.

The result of the comparison is either 0, if authentication was not successfully performed, or 1, ifauthentication was successful.

In fingerprint verification, the image system extracts the end and the bifurcation points of fingerlines, and uses location and direction as characteristic values for comparison with one or morestored references .

Generation of reference values and actual values is subject to distortion.

The comparison of the data sets is rather complete and introduces additional errors. Therefore, there is always the probability that biometrics authentication will fail, causing major

inconvenience to the user.

The false accept rate (FAR) is the probability that the system will accept the wrong user. The falsereject rate (FRR) is the probability; that the system will reject the correct user.