FRR in Biometric Authentication Systems

False Rejection Rate (FRR)

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What is called the percentage of valid subjects that are falsely rejected by a Biometric Authentication system?

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Explanation.

The percentage of valid subjects that are falsely rejected is called the False Rejection Rate (FRR) or Type I Error.

Source: KRUTZ, Ronald L.

& VINES, Russel.

D., The CISSP Prep Guide: Mastering the Ten Domains of Computer Security, 2001, John Wiley & Sons, Page 38.

Biometric authentication systems are designed to identify individuals based on their unique physical or behavioral characteristics such as fingerprints, facial features, or voice patterns. These systems are widely used in various applications including access control, authentication, and identification. However, biometric systems are not 100% accurate and may produce errors in the identification process. One of the most critical performance metrics of a biometric system is its ability to accurately identify valid subjects and reject impostors.

The percentage of valid subjects that are falsely rejected by a biometric authentication system is called False Rejection Rate (FRR) or Type I Error. FRR measures the system's failure to recognize a genuine user, causing them to be rejected and denied access. The FRR is typically expressed as a percentage of the total number of identification attempts made by valid users.

For instance, if a biometric system is used by 1,000 people to gain access to a secure area and five valid users are falsely rejected by the system, then the FRR would be 0.5% (5/1000).

FRR is also known as Type I Error, which occurs when a null hypothesis is rejected when it is true. In the case of biometric authentication systems, the null hypothesis is that the user is genuine, and the system should accept the user. However, when the system falsely rejects a valid user, it is equivalent to rejecting the null hypothesis and concluding that the user is not genuine, resulting in Type I Error.

To reduce the FRR, biometric systems need to be tuned to minimize the threshold that determines whether a biometric sample matches a template. However, reducing the threshold may increase the False Acceptance Rate (FAR), which is another critical performance metric of biometric systems. FAR measures the system's failure to reject an impostor, causing them to be accepted and granted access.

In summary, False Rejection Rate (FRR) or Type I Error is the percentage of valid subjects that are falsely rejected by a biometric authentication system. Biometric systems need to balance the FRR and FAR to achieve optimal performance.