Fingerprint Hardening with Randomly Selected Chaff Minutiae

Since fingerprints provide a reliable alternative for traditional password based security systems, they gain industry and citizen acceptance. However, due to the higher uncertainty and inherent complexity associated with biometrics, using pure biometric traits does not present a reliable security system especially for large populations. This paper addresses this problem by proposing a hardening scheme which combines the fingerprint minutiae-based template and user-specific pseudo random data to enhance security. In the proposed scheme, a set of randomly selected user-specific chaff minutiae features are stored in a smartcard and a subset of this set is used at each acquisition. The set of chaff minutiae is combined with the template set and scrambled to form a fixed-length hardened feature. The graph based dynamic matching algorithm is transparent to the proposed hardening scheme anyhow it runs as if pure original template and query features are used. Our experiments show that biometric hardening reduces error rate to 0% with several orders of magnitude separation between genuine and impostor populations.