Protect both Integrity and Confidentiality in Outsourcing Collaborative Filtering Computations

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.