一种增强的个性化匿名隐私保护模型

被引:3
作者
刘英华 [1 ,2 ]
刘永彬 [1 ]
李广原 [1 ]
郭建威 [1 ]
机构
[1] 北京科技大学信息工程学院
[2] 中国青年政治学院
关键词
数据发布; 个性化隐私保护; 匿名; k-匿名;
D O I
10.19304/j.cnki.issn1000-7180.2011.08.002
中图分类号
TP309 [安全保密];
学科分类号
081201 ; 0839 ; 1402 ;
摘要
匿名模型是近年来隐私保护研究的热点技术之一,主要研究如何在数据发布中避免敏感数据的泄露,又能保证数据发布的高效用性.提出了一种个性化(α[s],l)-多样k-匿名模型,该方法将敏感属性泛化成泛化树,根据数据发布中隐私保护的具体要求,给各结点设置不同的α约束,发布符合个性化匿名模型的数据.该方法在保护隐私的同时进一步提高信息的个性化要求.实验结果表明,该方法提高了信息的有效性,具有很高的实用性.
引用
收藏
页码:4 / 8
页数:5
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