Privacy Preserving Large-Scale Rating Data Publishing

Abstract

Large scale rating data usually contains both ratings of sensitive and non-sensitive issues, and the ratings of sensitive issues belong to personal privacy. Even when survey participants do not reveal any of their ratings, their survey records are potentially identifiable by using information from other public sources. In order to protect the privacy in the large-scale rating data, it is important to propose new privacy principles which consider the properties of the rating data. Moreover, given the privacy principle, how to efficiently determine whether the rating data satisfied the required privacy principle is crucial as well. Furthermore, if the privacy principle is not satisfied, an efficient method is needed to securely publish the large-scale rating data. In this paper, all these problem will be addressed.