文章基本信息

标题：Differential Privacy via Weighted Sampling Set Cover
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作者：Zhonglian Hu ; Zhaobin Liu ; Yangyang Xu 等
期刊名称：International Journal of Security and Its Applications
印刷版ISSN：1738-9976
出版年度：2016
卷号：10
期号：4
页码：79-88
DOI：10.14257/ijsia.2016.10.4.09
出版社：SERSC
摘要：Differential privacy is a security guarantee model which widely used in privacy preserving data publishing, but the query result can't be used in data research directly, especially in high-dimensional datasets. To address this problem, we propose a dimensionality reduction method. The core idea of this method is using a series of low- dimensional datasets to reconstruct a high-dimensional dataset, it improves data availability eventually. The main issue of this method is the reconstruction integrity, so a special sampling via set cover model is proposed in this article, which builds a multidimensional composite marginal tables set as a new middleware in differential privacy model. As a result, any form of disjunctive queries can be answered, and the accuracy of data query is improved. The experiment results also show the effectiveness of our method in practice.
关键词：differential privacy; set cover; sampling