Privacy Preserving Inner Product of Vectors in Cloud Computing

Gang Sheng, Tao Wen, Quan Guo and Ying Yin

International Journal of Distributed Sensor Networks, 2014, vol. 10, issue 5, 537252

Abstract: The problem of privacy preserving inner product of vectors has been widely studied. Much work has been done on the scenario of two parties involved in the computation. In this paper, we consider the scenario where three parties are involved in the computing process of cloud computing. We propose a new privacy preserving scheme for inner product of two vectors in the cloud and give the correctness analysis and performance analysis for the scheme. The proposed scheme is based on homomorphic encryption, and the security can be guaranteed. Experiments show the efficiency of the scheme.

Date: 2014
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Persistent link: https://EconPapers.repec.org/RePEc:sae:intdis:v:10:y:2014:i:5:p:537252

DOI: 10.1155/2014/537252

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