摘要
隐私保护数据挖掘的目标是寻找一种数据集变换方法,使得敏感数据或敏感知识在实施数据挖掘的过程中不被发现。近年出现了大量相关算法,按照隐私保持技术可将它们分为基于启发式技术、基于安全多方技术和基于重构技术三种。结合目前研究的热点对关联规则和分类规则的隐私保护数据挖掘进行介绍,并给出算法的评估方法,最后提出了关联规则隐私保护数据挖掘未来研究工作的方向。
The objective of privacy preserving data mining(PPDM) is to find a way to manipulate the dataset, so that the sensitive message can' t be disclosed in data mining. There are lots of algorithms proposed in recent years, they can be classified as heuristic-based techniques, seure multiparty techniques and reconstruction-based techniques by the privacy preserving technique. It gave an overview of PPDM in terms of the classification above, and presented some evaluation standards. Furthermore, it showed the future work of association rules hiding.
出处
《计算机应用研究》
CSCD
北大核心
2008年第12期3550-3555,共6页
Application Research of Computers
基金
重庆市自然科学基金资助项目(CSTC
2007BB2178)
关键词
数据挖掘
隐私保护
启发式技术
安全多方技术
重构技术
data mining
privacy preserving
heuristic technology
seure multiparty technology
reconstruction technology