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Privacy-Preserving Biometric Authentication: Cryptanalysis and Countermeasures

Hui Zhang, Xuejun Li, Syh‐Yuan Tan, Ming Jie Lee, Zhe Jin

2023IEEE Transactions on Dependable and Secure Computing23 citationsDOI

Abstract

In this article, we cryptanalyzed a Verifiable Threshold Predicate Encryption (VTPE) enabled Privacy-Preserving Biometric Authentication (PPBA) protocol reported in IEEE-TDSC and revealed discrepancies between its security claims and our security analysis. To be precise, the underlying authentication and key agreement scheme which is based on a challenge-response mechanism and watermark signal unsatisfactorily meets the following security scenario: (a) resistance to man-in-the-middle attacks, (b) biometric template protection, and (c) user anonymity and untraceability. To address these issues, we utilize Physical Unclonable Functions (PUF) to design a PUF driven Verifiable Threshold Predicate Encryption (PUF-VTPE) scheme and a secure PPBA protocol. The PUF-VTPE-based PPBA protocol equips with dual authentication using biometric and mobile device, which offers strong authenticity before establishing the session key. Simultaneously, the non-invertible property of PUF protects the biometric templates in the physical layer. The proposed storage-free mechanism that hides the challenge of device PUF in biometric template alleviates data leakage caused by storage challenges in PUF-based authentication protocols. Moreover, the experimental analysis suggests that the proposed PPBA protocol possesses ISO/IEC 24745 criteria of non-invertibility, unlinkability, and revocability. Additionally, the proposed PPBA protocol reduces the computational cost by about 50% compared to that of the cryptanalyzed scheme.

Topics & Concepts

Computer scienceVerifiable secret sharingBiometricsCryptanalysisComputer securityAuthentication (law)EncryptionAuthentication protocolSecurity analysisReplay attackCryptographyInformation leakageComputer networkSet (abstract data type)Programming languagePhysical Unclonable Functions (PUFs) and Hardware SecurityIntegrated Circuits and Semiconductor Failure AnalysisAdversarial Robustness in Machine Learning
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