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计算机工程 ›› 2012, Vol. 38 ›› Issue (11): 251-253. doi: 10.3969/j.issn.1000-3428.2012.11.076

• 开发研究与设计技术 • 上一篇    下一篇

抵抗背景知识攻击的电子病历隐私保护新算法

陈 炜1,陈志刚1,邓小鸿2,黄伟琦1   

  1. (1. 中南大学软件学院,长沙 410083;2. 江西理工大学应用科学学院,江西 赣州 341000)
  • 收稿日期:2011-10-07 出版日期:2012-06-05 发布日期:2012-06-05
  • 作者简介:陈 炜(1987-),男,硕士研究生,主研方向:信息安全;陈志刚,教授、博士、博士生导师、CCF会员;邓小鸿,讲师、博士研究生、CCF会员;黄伟琦,硕士研究生
  • 基金资助:
    国家自然科学基金资助项目(61073186);湖南省科技厅基金资助重点项目;中南大学中央高校基本科研业务费专项基金资助项目(2011QNZT023)

Novel Algorithm on Electronic Medical Record Privacy Protection Against Background Knowledge Attack

CHEN Wei    1, CHEN Zhi-gang    1, DENG Xiao-hong    2, HUANG Wei-qi    1   

  1. (1. School of Software Engineering, Central South University, Changsha 410083, China; 2. School of Applied Science, Jiangxi University of Science of Technology, Ganzhou 341000, China)
  • Received:2011-10-07 Online:2012-06-05 Published:2012-06-05

摘要: 在区域医疗信息共享下,传统的匿名化隐私保护算法面对背景知识攻击时抵抗力较差。为此,提出一种敏感属性聚类匿名算法。利用敏感属性之间的关联进行微聚类,使等价组中敏感属性之间在相似性增大的同时存在差异性,从而较好地抵抗背景知识攻击,提高抗泄露风险能力。实验结果表明,该算法能减小数据信息表中的隐私泄露风险。

关键词: 区域医疗, 信息共享, 隐私保护, 信息聚类, 敏感属性, 背景知识

Abstract: In the regional medical information sharing situation, traditional anonymity privacy protection algorithm performs poor resistance when facing with background knowledge attack. So this paper introduces the anonymous sensitive attribute clustering algorithm. The algorithm uses the links between sensitive attributes to make micro-property clustering, it increases the similarity between the sensitive attributes in the equivalent group while remaining the difference between them. The algorithm can perform better resistance while facing background knowledge attack with improved ability to resistant the leakage risks. Experimental results show that the loss of privacy in the data sheet risk reduced substantially when using the algorithm.

Key words: regional medical treatment, information sharing, privacy protection, information clustering, sensitive attribute, background knowledge

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