摘要
针对多数隐私保护算法不能较好平衡数据精度和数据隐私保护程度的问题,从数据集中准标识属性与敏感属性的关联关系出发,提出一种基于关联规则的匿名算法。运用Aprior算法建立属性间的关联规则,利用互信息量度量其关联度,为准标识属性的分级分类提供依据,同时设置泛化边界与权重,以避免产生较大的匿名成本。实验结果表明,该算法能够减少数据损失,实现数据效用与隐私保护之间的均衡。
To address the problem that most privacy protection algorithms can not balance the data accuracy and data privacy protection degree,an anonymity algorithm based on association rules is proposed according to the association relation between quasi-identification attributes and sensitive attributes in data sets.The Aprior algorithm is used to establish the association rules between attributes,and the mutual information is used to measure the degree of association,which provides a basis for the classification of quasi-identification attributes.Also generalized boundaries and weights are set to avoid large anonymity costs.Experimental results show that the algorithm can reduce data loss and achieve the balancing between data utility and privacy protection.
作者
吴睿雪
彭长根
刘波涛
丁红发
谢明明
WU Ruixue;PENG Changgen;LIU Botao;DING Hongfa;XIE Mingming(College of Computer Science and Technology,Guizhou University,Guiyang 550025,China;Guizhou Provincial Key Laboratory of Big Data,Guizhou University,Guiyang 550025,China;Institute of Cryptography and Data Security,Guizhou University,Guiyang 550025,China;College of Mathematics and Statistics,Guizhou University,Guiyang 550025,China)
出处
《计算机工程》
CAS
CSCD
北大核心
2019年第11期126-132,共7页
Computer Engineering
基金
国家自然科学基金(61662009,61772008)
“十三五”国家密码发展基金(MMJJ20170129)
贵州省科技计划项目(黔科合基础[2016]2315,黔科合基础[2017]1045)
贵州省科技计划项目(黔科合重大专项[2017]3002,黔科合重大专项[2018]3001)
关键词
隐私保护
多敏感属性
关联关系
泛化边界
关联规则
privacy protection
multi-sensitive attribute
association relation
generalized boundary
association rule
