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False acceptance is an error in biometrics that causes an unauthorized person to be authenticated. Biometrics uses distinguishing human characteristics as a mode of authentication, such as fingerprints or voice. False acceptance is the most serious biometric security problem, as it permits unauthorized users to access sensitive systems.
For example, assume that User A owns a laptop, which boots using a fingerprinting mechanism. User B tries to log on to User A’s laptop. If User B succeeds, this is false acceptance. In reality, no biometric system is ideal, so the best designers can do is to minimize false positive results.
One way of determining the accuracy of a biometric system is by calculating the false acceptance ratio. An independent trial may be conducted to test the system, using people with different physical characteristics. To obtain an accurate reading, many participants need to be involved. Facial recognition can fail in low light conditions due to poor picture quality. Similarly, voice recognition systems may fail in a noisy environment. Testing helps determine situations where false positives are likely to occur and thus minimize them.