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中文摘要：
组织发布数据过程产生的隐私保护问题（Privacy Preserving in Data Published,PPDP）是数据挖掘和信息安全领域近几年来的研究热点。对数据施加匿名处理是微观数据发布过程保护数据主体隐私信息的有效方法之一。阐述了隐私保护问题的内涵,归纳了发布数据可能遭受的攻击类型,分析了常用的匿名技术,比较了匿名发布表质量度量方法,指出匿名方法应用于数据发布隐私保护的热点研究方向。
英文摘要：
In recent years,many data sets are accessed by the commons for purpose of research,cooperation and e-business.Releasing data about individuals without revealing their private information has become an active issue,and k-anonymous-based models are effective techniques that prevent linking attack.This paper introduced the concept of privacy preserving,induced the type of attack,summarized the algorithms and models based on the k-anonymity,and compared the measure criteria of published table.And finally the directions of this area were concluded.
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