Reference : Protect both Integrity and Confidentiality in Outsourcing Collaborative Filtering Com... |
Scientific congresses, symposiums and conference proceedings : Unpublished conference | |||
Engineering, computing & technology : Computer science | |||
Security, Reliability and Trust | |||
http://hdl.handle.net/10993/29388 | |||
Protect both Integrity and Confidentiality in Outsourcing Collaborative Filtering Computations | |
English | |
Pejo, Balazs ![]() | |
Tang, Qiang ![]() | |
Wang, Husen ![]() | |
27-Jun-2016 | |
Yes | |
International | |
9th IEEE International Conference on Cloud Computing (IEEE CLOUD) | |
June 27 - July 2, 2016 | |
San Francisco | |
United States of America | |
[en] Collaborative Filtering ; Integrity ; Verification | |
[en] 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, the integrity of computation results needs 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. We then propose a new solution to outsource all computations of the weighted Slope One algorithm in two-server setting and provide experimental results. | |
http://hdl.handle.net/10993/29388 |
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