差分隐私保护在数据挖掘中应用综述

doi:10.6040/j.issn.1671-9352.2.2016.053

摘要/Abstract

摘要： 针对差分隐私在数据挖掘中的最新成果进行了研究,介绍了差分隐私保护的定义和实现机制,分析了差分隐私在模式挖掘、分类和聚类中的相关研究,着重解析了部分重要技术的实现原理,对比分析了其优缺点和算法复杂度。最后,展望了差分隐私在动态数据发布和大数据环境下的研究方向。

关键词: 隐私保护, 信息安全, 差分隐私, 数据挖掘

Abstract: The latest results of differential privacy in data mining were surveyed. The basic concepts of differential privacy were introduced. It analyzes the differential privacys research in pattern mining, classification and cluster. It was focused that on the analysis of the principle of some important technology to achieve. And also it was made that comparative analysis of its strengths and weaknesses and algorithm complexity. Finally, the future research of difference privacy under the dynamic data publication and big data environments was discussed.

Key words: differential privacy, privacy preserving, information security, data mining

中图分类号:

TP309

康海燕,马跃雷. 差分隐私保护在数据挖掘中应用综述[J]. 山东大学学报（理学版）, 2017, 52(3): 16-23.

KANG Hai-yan, MA Yue-lei. Survey on application of data mining via differential privacy[J]. JOURNAL OF SHANDONG UNIVERSITY(NATURAL SCIENCE), 2017, 52(3): 16-23.

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