Identification and secret-key binding in binary-symmetric template-protected biometric systems

In the system that we investigate here, two terminals observe the enrollment and identification biometric sequences of different individuals. The first terminal binds a secret key to each enrolled individual and stores the corresponding helper data in a public database. These helper data, on one hand, facilitate reliable determination of the individual's identity for the second terminal, and, on the other hand, reliable reconstruction of the secret key of this individual, based on the presented biometric identification sequence. All helper data in the database are assumed to be public. Since the secret keys are used by the individuals e.g. to encrypt data, the helper data should provide no information on these secret keys. In this paper we determine what identification and secret-key rates can be jointly realized by such a biometric identification and key-binding system. We focus on the binary symmetric case and show that there exist linear codes yielding optimal performance. The setting that we investigate here is closely related to the study of the biometric identification capacity [O'Sullivan and Schmid, 2002, Willems et al., 2003] and the common randomness generation problem [Ahlswede and Csiszár, 1993]. The linear-coding part generalizes the fuzzy commitment scheme [Juels and Wattenberg, 1999].