电子学报Issue(9)：1718-1723,6.DOI:10.3969/j.issn.0372-2112.2014.09.009
基于属性相关性划分的多敏感属性隐私保护方法
A Privacy Preserving Approach Based on Attributes Correlation Partition for Multiple Sensitive Attributes
摘要
Abstract
In recent years ,l-diversity models are suitable not only for single sensitive attribute data tables ,but also for multi-ple sensitive attributes data tables .However ,most of the research is based on lossy join ,it breaks the relationship between data .To address these problems ,a model based on multiple sensitive attributes is proposed .The main idea of the model is that it proposes a l-maximum principle that can satisfy the multiple sensitive attributes l-diversity at first .Then ,to protect the relationship between da-ta ,the model partitions attributes by the dependency degree between attributes .Finally ,a multiple sensitive attributes l-maximum al-gorithm (MSA l-maximum )is proposed .The experiment results show that the proposed model can preserve the security of sensitive data ,meanwhile it can also reduce the information hidden rate and keep a high data utility .关键词
隐私保护/多敏感属性/l-多样性/属性相关性/划分Key words
privacy preserving/multiple sensitive attributes/l-diversity/attributes correlation/partition分类
信息技术与安全科学引用本文复制引用
谢静,张健沛,杨静,张冰..基于属性相关性划分的多敏感属性隐私保护方法[J].电子学报,2014,(9):1718-1723,6.基金项目
国家自然科学基金（ No ．61370083，No ．61073043，No ．61073041）；高等学校博士学科点专项科研基金（ No ．20112304110011，No ．20122304110012）；哈尔滨市科技创新人才研究专项资金（优秀学科带头人） （）
