Hybrid Protection of Biometric Templates by Combining Homomorphic Encryption and Cancelable Biometrics

Shahreza, Hatef Otroshi; Rathgeb, Christian; Osorio-Roig, Daile; Hahn, Vedrana Krivokuca; Marcel, Sébastien; Busch, Christoph

doi:10.1109/ijcb54206.2022.10007960

Cited by 15 publications

(8 citation statements)

References 35 publications

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“…Shahreza et al [ 58 ] proposed a hybrid solution to securing face templates by combining the cancelable biometric (CB) technique and HE. Since the protected templates are irreversible even in the case of a compromised secret key (often referred to as the fully compromised case), using CB prior to HE strengthens the security and privacy of the whole system and reduces template dimensions, which accelerates the computation of ciphertexts.…”

Section: He-based Approaches To Biometric Securitymentioning

confidence: 99%

A Review of Homomorphic Encryption for Privacy-Preserving Biometrics

Yang

Wang

Cui

et al. 2023

Sensors

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The advancement of biometric technology has facilitated wide applications of biometrics in law enforcement, border control, healthcare and financial identification and verification. Given the peculiarity of biometric features (e.g., unchangeability, permanence and uniqueness), the security of biometric data is a key area of research. Security and privacy are vital to enacting integrity, reliability and availability in biometric-related applications. Homomorphic encryption (HE) is concerned with data manipulation in the cryptographic domain, thus addressing the security and privacy issues faced by biometrics. This survey provides a comprehensive review of state-of-the-art HE research in the context of biometrics. Detailed analyses and discussions are conducted on various HE approaches to biometric security according to the categories of different biometric traits. Moreover, this review presents the perspective of integrating HE with other emerging technologies (e.g., machine/deep learning and blockchain) for biometric security. Finally, based on the latest development of HE in biometrics, challenges and future research directions are put forward.

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Section: He-based Approaches To Biometric Securitymentioning

confidence: 99%

A Review of Homomorphic Encryption for Privacy-Preserving Biometrics

Yang

Wang

Cui

et al. 2023

Sensors

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“…3) Implementation details and Source-code: In our experiments, we use the Bob 9 toolbox [46], [47] to both build the biometric recognition systems and generate mated and nonmated pairs. In addition, we use the open-source implementations (in Bob) of the BioHashing, MLP-Hash, IoM-GRP, IoM-URP, Bloom Filters, and HE schemes [35], [48]- [52]. For the implementation of HE, we use its implementation in Bob [52] using the SEAL-Python 10 wrapper on Python 3.8 for the C++ SEAL library [53].…”

Section: A Experimental Setupmentioning

confidence: 99%

“…In addition, we use the open-source implementations (in Bob) of the BioHashing, MLP-Hash, IoM-GRP, IoM-URP, Bloom Filters, and HE schemes [35], [48]- [52]. For the implementation of HE, we use its implementation in Bob [52] using the SEAL-Python 10 wrapper on Python 3.8 for the C++ SEAL library [53]. The source code of all our experiments is publicly available to help researchers reproduce our results as well as to allow them to use our method to measure the linkability of their own protected templates 11 .…”

Section: A Experimental Setupmentioning

confidence: 99%

Measuring Linkability of Protected Biometric Templates Using Maximal Leakage

Shahreza

Shkel

Marcel

2023

IEEE Trans.Inform.Forensic Secur.

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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 wellstudied 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.

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“…prediction of soft-biometric attributes. Motivated by that fact that homomorphic encryption does not achieve irreversibility when the secret k is known to an attacker, researchers have recently proposed to apply homomorphic encryption on top of cancelable biometrics [87], [88]. Thereby, some protection is retained, even in the full disclosure attack model.…”

Section: Further Workmentioning

confidence: 99%