Abstract
Biometric identification (BI) is the task of searching a pre-established biometric database to find a matching record for an enquiring biometric trait sampled from an unknown individual of interest. This has recently been aided with cloud computing, which brings a lot of convenience but simultaneously arouses new privacy concerns. Two cloud aided BI schemes pursuing privacy preserving have recently been proposed by Wang et al. in ESORICS ’15. In this paper, we propose several elaborately designed attacks to reveal the security breaches in these two schemes. Theoretical analysis is given to validate our proposed attacks, which indicates that via such attacks the cloud server can accurately infer the outsourced database and the identification request.
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Acknowledgment
The authors would like to thank the anonymous reviewers for their valuable comments. This work was supported by the National Natural Science Foundation of China under Grant 61272479, the National 973 Program of China under Grant 2013CB338001, and the Strategic Priority Research Program of Chinese Academy of Sciences under Grant XDA06010702
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Pan, S., Yan, S., Zhu, WT. (2016). Security Analysis on Privacy-Preserving Cloud Aided Biometric Identification Schemes. In: Liu, J., Steinfeld, R. (eds) Information Security and Privacy. ACISP 2016. Lecture Notes in Computer Science(), vol 9723. Springer, Cham. https://doi.org/10.1007/978-3-319-40367-0_29
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DOI: https://doi.org/10.1007/978-3-319-40367-0_29
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