[Resource Topic] 2016/079: Protect both Integrity and Confidentiality in Outsourcing Collaborative Filtering Computations

Welcome to the resource topic for 2016/079

Title:
Protect both Integrity and Confidentiality in Outsourcing Collaborative Filtering Computations

Authors: Qiang Tang, Balazs Pejo, Husen Wang

Abstract:

In the cloud computing era, in order to avoid the computational burdens, many recommendation service providers tend to outsource their collaborative filtering computations to third-party cloud servers. In order to protect service quality and privacy for end users, both the integrity of computation results and the confidentiality of original dataset need to be guaranteed. In this paper, we analyze two integrity verification approaches by Vaidya et al. and demonstrate their performances. In particular, we analyze the verification via auxiliary data approach which is only briefly mentioned in the original paper, and demonstrate the experimental results (with better performances). We then propose a new solution to outsource all computations of the weighted Slope One algorithm in multi-server setting and provide experimental results. We finally discuss the possibility of using homomorphic encryption to achieve both integrity and confidentiality guarantees.

ePrint: https://eprint.iacr.org/2016/079

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