Compare Accuracy of Biometric Authentication Devices

A.

equal error rate or crossover error rate (EER or CER): the rate at which both accept and reject errors are equal.

The value of the EER can be easily obtained from the ROC curve.

The EER is a quick way to compare the accuracy of devices with different ROC curves.

In general, the device with the lowest EER is most accurate.

In the context of Biometric Authentication almost all types of detection permit a system's sensitivity to be increased or decreased during an inspection process.

If the system's sensitivity is increased, such as in an airport metal detector, the system becomes increasingly selective and has a higher False Reject Rate (FRR)

Conversely, if the sensitivity is decreased, the False Acceptance Rate (FAR) will increase.

Thus, to have a valid measure of the system performance, the CrossOver Error Rate (CER) is used.

The following are used as performance metrics for biometric systems: false accept rate or false match rate (FAR or FMR): the probability that the system incorrectly matches the input pattern to a non-matching template in the database.

It measures the percent of invalid inputs which are incorrectly accepted.

In case of similarity scale, if the person is imposter in real, but the matching score is higher than the threshold, then he is treated as genuine that increase the FAR and hence performance also depends upon the selection of threshold value.

false reject rate or false non-match rate (FRR or FNMR): the probability that the system fails to detect a match between the input pattern and a matching template in the database.

It measures the percent of valid inputs which are incorrectly rejected.

failure to enroll rate (FTE or FER): the rate at which attempts to create a template from an input is unsuccessful.

This is most commonly caused by low quality inputs.

failure to capture rate (FTC): Within automatic systems, the probability that the system fails to detect a biometric input when presented correctly.

template capacity: the maximum number of sets of data which can be stored in the system.

Reference(s) used for this question: KRUTZ, Ronald L.

& VINES, Russel.

D., The CISSP Prep Guide: Mastering the Ten Domains of Computer Security, 2001, John Wiley & Sons, Page 37

and Wikipedia at:https://en.wikipedia.org/wiki/Biometrics.

In the context of biometric authentication, accuracy is typically measured by evaluating two types of errors: false acceptance (FA) and false rejection (FR).

False acceptance rate (FAR) is the probability that a biometric system incorrectly accepts an unauthorized user, while false rejection rate (FRR) is the probability that the system incorrectly rejects an authorized user.

The correct answer to the question is C. FAR is used to compare accuracy of devices because it represents the probability of the system allowing an unauthorized user to access a secure system. In other words, the lower the FAR, the less likely it is that an unauthorized user will be granted access, indicating a more accurate device.

Comparing devices based on FRR is not appropriate because this would only reflect how often authorized users are incorrectly rejected, not how often unauthorized users are correctly rejected.

Similarly, FER (false error rate) is not a commonly used term in biometric authentication, and CER (cross error rate) is a metric used to compare the accuracy of different algorithms rather than devices.

In summary, the FAR is the appropriate metric to compare the accuracy of biometric authentication devices, with lower values indicating greater accuracy.