Preventing the Decodability Attack Based Cross-Matching in a Fuzzy Commitment Scheme

Abstract

Template protection techniques are used within biometric systems in order to safeguard the privacy of the system's subjects. This protection also includes unlinkability, i.e., preventing cross-matching between two or more reference templates from the same subject across different applications. In the literature, the template protection techniques based on fuzzy commitment, also known as the code-offset construction, have recently been investigated. Recent work presented the decodability attack vulnerability facilitating cross-matching based on the protected templates and its theoretical analysis. First, we extend the theoretical analysis and include the comparison between the system and cross-matching performance. We validate the presented analysis using real biometric data from the MCYT fingerprint database. Second, we show that applying a random bit-permutation process secures the fuzzy commitment scheme from cross-matching based on the decodability attack.