一种基于有损连接的个性化隐私保护方法

计算机科学 ›› 2013, Vol. 40 ›› Issue (Z6): 349-353.

一种基于有损连接的个性化隐私保护方法

刘英华

中国青年政治学院北京100089

出版日期:2018-11-16 发布日期:2018-11-16
基金资助:
本文受国家自然科学基金项目(61175048)资助

Personalized Privacy Preserving Method Based on Lossy Join

LIU Ying-hua

Online:2018-11-16 Published:2018-11-16

摘要/Abstract

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既能避免敏感数据泄露,又能保证数据发布的高效用性。提出了一种(α[s],k)-匿名有损分解模型,该模型通过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个性化α约束；基于数据库有损分解思想,将数据分解成敏感信息表和非敏感信息表,利用有损连接生成的冗余信息实现隐私保护。实验结果表明,该模型很好的个性化保护了数据隐私。

关键词: 数据发布,隐私保护,数据挖掘,有损连接,k-匿名

Abstract: Recently,anonymity model is one of the hot topic techniques in privacy preserving research．The mainly research is how to avoid leakage of sensitive data in data publishing,but also ensures the efficient use of data．This paper proposed a personalized(α[s],k) - lossy decomposition anonymity model．This method publishes the personalized data though generalization technology and personalizedα restriction for different code of the generalization tree．Based on the idea of lossy decomposition in database,data is projected into the sensitive information table and non sensitive information table,and then the redundant information can be realized privacy protection．Experimental results show that the model can provide better privacy.

Key words: Data dissemination,Privacy preserving,Data mining,Lossy join,k-anonymity

刘英华. 一种基于有损连接的个性化隐私保护方法[J]. 计算机科学, 2013, 40(Z6): 349-353. https://doi.org/

LIU Ying-hua. Personalized Privacy Preserving Method Based on Lossy Join[J]. Computer Science, 2013, 40(Z6): 349-353. https://doi.org/

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