期刊名称：International Journal of Innovative Research in Computer and Communication Engineering
印刷版ISSN：2320-9798
电子版ISSN：2320-9801
出版年度：2014
卷号：2
期号：7
出版社：S&S Publications
摘要：We propose secure multi-party computation protocols for collaborative data publishing with m-privacy.All protocols are extensively analyzed and their security and efficiency are formally proved. Experiments on real-lifedatasets suggest that our approach achieves better or comparable utility and efficiency than existing and baselinealgorithms while satisfying m-privacy. We consider the collaborative data publishing problem for anonym zinghorizontally partitioned data at multiple data providers. We consider a new type of “insider attack” by colluding dataproviders who may use their own data records (a subset of the overall data) to infer the data records contributed by otherdata providers. The paper addresses this new threat, and makes several contributions. First, we introduce the notion ofm-privacy, which guarantees that the anonym zed data satisfies a given privacy constraint against any group of up to mcolluding data providers. Second, we present heuristic algorithms exploiting the monotonicity of privacy constraints forefficiently checking m-privacy given a group of records. Third, we present a data provider-aware anonymizationalgorithm with adaptive m-privacy checking strategies to ensure high utility and m-privacy of anonym zed data withefficiency.
