计算机应用研究2013，Vol.30Issue(2)：518-520,3.DOI:10.3969/j.issn.1001-3695.2013.02.055
基于模糊集的隐私保护方法研究
Fuzzy-based methods for privacy preserving
摘要
Abstract
This paper did research based on fuzzy sets to overcome the high complexity, low efficiency and poor data availability of k-anonymity in the research of privacy-preserving data publishing. It focused on the processing of numerical attributes, and proposed the maximal membership degree algorithm. It fuzzed sensitive numerical attributes to semantic data which was released combining with membership degree. Verified through experiments, compared with k-anonymity methods, the MMD has better efficiency, furthermore, its information losses will be far smaller than k-anonymity and the availability of released data is better.关键词
隐私保护/模糊集/模糊化/隶属函数/隶属度/k-匿名Key words
privacy preserving/fuzzy sets/fuzzed/membership function/membership degree/k-anonymity分类
信息技术与安全科学引用本文复制引用
王茜,杨传栋,刘泓..基于模糊集的隐私保护方法研究[J].计算机应用研究,2013,30(2):518-520,3.
