J4 ›› 2011, Vol. 46 ›› Issue (5): 82-85.
• SEWM 2011 会议 • 上一篇 下一篇
李立,袁方,郗亚辉
收稿日期:
发布日期:
作者简介:
基金资助:
河北省教育厅科学研究重点项目(ZH200804)
LI Li, YUAN Fang, XI Ya-hui
Received:
Published:
摘要：
将现有的敏感属性隐私保护方法直接应用于相关多敏感属性的隐私保护中会导致隐私数据的泄漏。本文借鉴有损连接对隐私数据进行保护的思想,对表中的记录进行聚类,保证了关系表中的记录按敏感等级划分。其次,对已划分的记录按照频率比较策略进行分组,提出了一种基于聚类的相关多敏感属性数据分组算法。实验结果表明该算法可以有效地防止隐私泄露,增强了数据发布的安全性。
关键词: 数据隐私;相关多敏感属性;k多样性;独立相关;联合相关
Abstract:
Directly applying the existing sensitive attribute privacy protection methods to multiple sensitive attributes privacy protection can divulge the privacy data. Firstl, the thought of lossy join to protect privacy data was inherited, and the records of tables were clustered to guarantee the sensitive rank division in tables. Then, the records were grouped according to the frequency of comparative strategy. And a grouping algorithm aimed at data containing multi-sensitive attributes was proposed based on the cluster. Experimental results indicated that this algorithm could prevent the privacy revelation and strengthen the security of data published.
Key words: data privacy; relational multi-sensitive attribute; k-diversity; independent relational; joint relational
李立,袁方,郗亚辉. 面向相关多敏感属性的隐私保护方法[J]. J4, 2011, 46(5): 82-85.
LI Li, YUAN Fang, XI Ya-hui. Privacy preserving approaches for relational multiple sensitive attributes[J]. J4, 2011, 46(5): 82-85.
0 / / 推荐
导出引用管理器 EndNote|Reference Manager|ProCite|BibTeX|RefWorks
链接本文: http://lxbwk.njournal.sdu.edu.cn/CN/
http://lxbwk.njournal.sdu.edu.cn/CN/Y2011/V46/I5/82
Cited
