During a quarterly security audit, the facilities team wants to know how often the biometric fingerprint readers at each data-center entrance mistakenly permit an individual who is not enrolled in the system. Which biometric performance metric best quantifies this specific risk?
The metric that measures the probability that an unauthorized (impostor) subject is incorrectly granted access by a biometric system is the false acceptance rate. It directly tracks instances where a reader matches a presented template to a stored template that does not belong to the user, so it is the most relevant value for assessing how frequently attackers might slip through. The false rejection rate instead tracks how often legitimate users are denied, the crossover (or equal) error rate shows the point where false accepts and false rejects are equal-useful for tuning but not for measuring one class of error in isolation-and the failure to enroll rate concerns problems during the initial registration process, not day-to-day access decisions.
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What is the false acceptance rate (FAR) and why is it significant?
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How does the false rejection rate (FRR) differ from the false acceptance rate (FAR)?
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What is the crossover error rate (CER) and how is it used in biometric systems?