隐私保护数据挖掘研究进展

近年来隐私保护数据挖掘已经成为数据挖掘的研究热点, 并取得了丰富的研究成果。但是, 随着移动通信、嵌入式、定位等技术的发展与物联网、位置服务、基于位置的社交网络等应用的出现, 具有个人隐私的信息内容更加丰富, 利用数据挖掘工具对数据进行综合分析更容易侵犯个人隐私。针对新的应用需求, 对隐私保护数据挖掘方法进行深入研究具有重要的现实意义。在分析现有的隐私保护数据挖掘方法分类与技术特点的基础上, 提出现有方法并应用于新型分布式系统架构应用系统、高维数据及时空数据等领域存在的挑战性问题, 并指出了今后研究的方向。

Research advances on privacy-preserving data mining

In recent years, the privacy-preserving data mining has become a hotspot in data mining. However, with the development of technologies (mobile communication, embedded and positioning technologies, etc), the emerging applications(the Internet of things, location-based services, social network based on location, etc) result in accumulation of abundant personal privacy information, which will easily lead to the violence of personal privacy. Therefore, it is significant to study the privacy-preserving data mining methods to meet the demands of new appplications. In view of the analyzing the characteristics and catalogs of existing privacy-preserving data mining methods, this paper proposed their challenges from the field of new distributed system, high dimensional data and spatio-temporal data, etc, as well as indicatef the future research directions.