Direct biometric verification schemes with Gaussian data

Verification of the person's identity using the database, which contains outcomes of his biometric measurements, is considered. The verification algorithm is proposed and its performance is evaluated with the assumption that the input data represent the vector of values of a random variable generated according to the Gaussian probability distribution and observed under an additive white Gaussian noise. The evaluation of the false acceptance rate includes an analysis of the possibilities of attackers, called wolves, who generate fixed vectors that have the best chance for the verifier's acceptance decision when the biometrics of the person is unknown.