Privacy-Enhanced Profile-Based Authentication Using Sparse Random Projection

Abstract : In a profile-based authentication system, a user profile is stored at the verifier and later used to verify their authentication claim. A profile includes user-specific information that is privacy sensitive. In this paper we propose a non-cryptographic approach to providing privacy for user profile data in profile-based authentication systems, using an efficient construction of random projection: a linear dimension reducing transform that projects the profile and the verification data to a lower dimension space, while preserving relative distances of the vectors and so correctness of authentication. We define privacy measures for two types of profiles: a single vector profile and a multivector profile, derive theoretical bounds on the privacy and correctness of privacy enhanced systems, and verify the results experimentally on two profile-based authentication systems: a face-biometric system  and a behavioural based authentication system. We discuss our results and propose directions for future research.
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Submitted on : Monday, November 27, 2017 - 10:32:15 AM
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Somayeh Taheri, Md Islam, Reihaneh Safavi-Naini. Privacy-Enhanced Profile-Based Authentication Using Sparse Random Projection. 32th IFIP International Conference on ICT Systems Security and Privacy Protection (SEC), May 2017, Rome, Italy. pp.474-490, ⟨10.1007/978-3-319-58469-0_32⟩. ⟨hal-01649016⟩

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