摘要
在隐私保护的数据发布研究中,目前的方法通常都是先删除身份标识属性,然后对准标识属性进行匿名处理.分析了单一个体对应多个记录的情况,提出了一种保持身份标识属性的匿名方法,它在保持隐私的同时进一步提高了信息有效性.采用概化和有损连接两种实现方式.实验结果表明,该方法提高了信息有效性,具有很好的实用性.
In the research of privacy preserving data publishing, the present method always removes the individual identification attributes and then anonymizes the quasi-identifier attributes. This paper analyzes the situation of multiple records one individual and proposes the principle of identity-reserved anonymity. This method reserves more information while maintaining the individual privacy. The generalization and loss-join approaches are developed to meet this requirement. The algorithms are evaluated in an experimental scenario, reserving more information and demonstrating practical applicability of the approaches.
出处
《软件学报》
EI
CSCD
北大核心
2010年第4期771-781,共11页
Journal of Software
基金
国家自然科学基金No.60403041~~
关键词
隐私保护
数据发布
匿名
身份保持
有损连接
概化
privacy preservation
data publishing
anonymity
identity-reserved
lossyjoin
generalization