Correctness Verification of Outsourced Inner Product of Vectors with Error Localization

Abstract

Security challenges are the vital issues to be addressed in the research arena of cloud computing, among which the data security plays an important role. The technique of correctness verification enables the cloud user to check whether or not the returned results by the cloud service provider are correct. Inner product of vectors, i.e. weighted sum, is studied and applied in wide area, such as similar document detection, face recognition, etc. In this paper, we aim at the goal of result correctness verification with error localization of the outsourced inner products of vectors in the cloud. Our proposed scheme can help the cloud user to verify the correctness of the results. Further more, the cloud user can localize which result(s) is(are) incorrect if the results are checked to be incorrect. The efficiency analysis show the running efficiency of the proposed scheme.