Ensemble Performance of Biometric Authentication Systems Based on Secret Key Generation

We study the ensemble performance of biometric authentication systems, based on secret key generation, which work as follows. In the enrollment stage, an individual provides a biometric signal that is mapped into a secret key and a helper message, the former being prepared to become available to the system at a later time (for authentication), and the latter is stored in a public database. When an authorized user requests authentication, claiming his/her identity as one of the subscribers, he/she has to provide a biometric signal again, and then the system, which retrieves also the helper message of the claimed subscriber, produces an estimate of the secret key, that is finally compared with the secret key of the claimed user. In case of a match, the authentication request is approved, otherwise, it is rejected. Referring to an ensemble of systems based on Slepian-Wolf binning, we provide a detailed analysis of the false-reject (FR) and false-accept (FA) probabilities, for a wide class of stochastic decoders. We also derive converse bounds. The converse bound of the FA probability matches the direct theorem, whereas the one for the FR probability is tight for some ranges of rates. Finally, we outline derivations of the secrecy leakage (for the typical code in the ensemble) and the privacy leakage.