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- W4377079735 abstract "Privacy-preserving Verifiable (outsourced) Computation (PVC) for face recognition is a significant research topic in the information security community. Recently, an efficient elementary matrices masking-based PVC protocol for face recognition has been published in IEEE Transactions on Dependable and Secure Computing [2]. In this paper, we analyze the privacy property of this protocol, and demonstrate that the output distribution of the problem generation algorithm in this protocol is not computationally indistinguishable from the uniform distribution over a matrix set, which breaks the original consequence (see Theorem 1). We introduce a formal definition of a privacy model for a PVC protocol and prove that the targeted PVC protocol does not hold privacy under this model. We then present our experimental results to support our theoretical analyses." @default.
- W4377079735 created "2023-05-20" @default.
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- W4377079735 date "2023-01-01" @default.
- W4377079735 modified "2023-09-29" @default.
- W4377079735 title "On the Privacy of Elementary Matrices Masking-Based Verifiable (Outsourced) Computation" @default.
- W4377079735 doi "https://doi.org/10.1109/tdsc.2023.3277285" @default.
- W4377079735 hasPublicationYear "2023" @default.
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