Symmetric hash functions for secure fingerprint biometric systems

Authors:
Sergey Tulyakov;Faisal Farooq;Praveer Mansukhani;Venu Govindaraju
Affiliations:
Center for Unified Biometrics and Sensors, State University of New York at Buffalo, Amherst, NY 14228, USA;Center for Unified Biometrics and Sensors, State University of New York at Buffalo, Amherst, NY 14228, USA;Center for Unified Biometrics and Sensors, State University of New York at Buffalo, Amherst, NY 14228, USA;Center for Unified Biometrics and Sensors, State University of New York at Buffalo, Amherst, NY 14228, USA
Venue:
Pattern Recognition Letters
Year:
2007

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Abstract

Securing biometrics databases from being compromised is an important research challenge that must be overcome in order to support widespread use of biometrics based authentication. In this paper we present a novel method for securing fingerprints by hashing the fingerprint minutia and performing matching in the hash space. Our approach uses a family of symmetric hash functions and does not depend on the location of the (usually unstable) singular points (core and delta) as is the case with other methods described in the literature. It also does not assume a pre-alignment between the test and the stored fingerprint templates. We argue that these assumptions, which are often made, are unrealistic given that fingerprints are very often only partially captured by the commercially available sensors. The Equal Error Rate (EER) achieved by our system is 3%. We also present the performance analysis of a hybrid system that has an EER of 1.96% which reflects almost no drop in performance when compared to straight matching with no security enhancements. The hybrid system involves matching using our secure algorithm but the final scoring reverts to that used by a straight matching system.