计算机应用与软件2024，Vol.41Issue(5)：319-326,8.DOI:10.3969/j.issn.1000-386x.2024.05.046
基于敏感分级信息熵的匿名方法
DATA ANONYMITY METHOD BASED ON SENSITIVE HIERARCHICAL INFORMATION ENTROPY
摘要
Abstract
Aiming at the problem of privacy leakages caused by similar attacks,this paper proposes(H,p,k)-anonymous model.By classifying sensitive attributes,the number of tuples with different sensitive level in equivalent classes could meet the set threshold H.An anonymous algorithm MAA-SLIE(micro-aggregation algorithm based on sensitive level information entropy)was designed to satisfy the model.Based on the greedy clustering idea,the algorithm ensured the maximum privacy security index of the equivalence class in the clustering process,improved the diversity of sensitive attributes in the equivalence class,and reduced the risk of privacy leakage and information loss.The rationality and effectiveness of the algorithm were verified through experiments.关键词
数据匿名/信息熵/微聚集/隐私保护Key words
Data anonymity/Information entropy/Micro-aggregation/Privacy protection分类
信息技术与安全科学引用本文复制引用
石昆正,张攀峰,董明刚..基于敏感分级信息熵的匿名方法[J].计算机应用与软件,2024,41(5):319-326,8.基金项目
国家自然科学基金项目(61862019) （61862019）
广西自然科学基金项目(2017GXNSFAA198223) （2017GXNSFAA198223）
广西科技基地和人才专项(2018AD19136) （2018AD19136）
桂林理工大学科研启动基金项目(GLUTQD2017065). （GLUTQD2017065）
