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@ARTICLE{OtroshiShahreza_IEEE-TIFS_2023,
         author = {Otroshi Shahreza, Hatef and Shkel, Yanina Y. and Marcel, S{\'{e}}bastien},
       keywords = {biometric template protection, Biometrics, Differential Privacy, linkability, maximal leakage, statistical hypothesis testing, template},
          title = {Measuring Linkability of Protected Biometric Templates Using Maximal Leakage},
        journal = {IEEE Transactions on Information Forensics and Security},
         volume = {18},
           year = {2023},
          pages = {2262 - 2275},
            url = {https://ieeexplore.ieee.org/abstract/document/10098649},
            doi = {10.1109/TIFS.2023.3266170},
       abstract = {As the applications of biometric recognition systems are increasing rapidly, there is a growing need to secure the sensitive data used within these systems. Considering privacy challenges in such systems, different biometric template protection (BTP) schemes were proposed in the literature, and the ISO/IEC 24745 standard defined a number of requirements for protecting biometric templates. While there are several studies on evaluating different requirements of the ISO/IEC 24745 standard, there have been few studies on how to measure the linkability of biometric templates. In this paper, we propose a new method for measuring linkability of protected biometric templates. The proposed method is based on maximal leakage, which is a well-studied measure in information-theoretic literature. We show that the resulting linkability measure has a number of important theoretical properties and an operational interpretation in terms of statistical hypothesis testing. We compare the proposed measure to two other linkability measures: one previously introduced in the literature, and a similar measure based on differential privacy. In our experiments, we use the proposed measure to evaluate the linkability of biometric templates from different biometric characteristics (face, voice, and finger vein), which are protected with different BTP schemes. The source codes of our proposed measure and all experiments are publicly available.}
}