面向缺损敏感属性的加权信息熵匿名算法  

A WEIGHTED INFORMATION ENTROPY ANONYMOUS ALGORITHM FOR DEFECT SENSITIVE ATTRIBUTES

作　　者：敬超[1,2,3] 肖链 谭华 张攀峰 Jing Chao;Xiao Lian;Tan Hua;Zhang Panfeng(College of Information Science and Engineering,Guilin University of Technology,Guilin 541006,Guangxi,China;Guangxi Key Laboratory of Embedded Technology and Intelligent System,Guilin 541004,Guangxi,China;Guangxi Key Laboratory of Trusted Software,Guilin 541004,Guangxi,China;School of Electronic Information and Automation,Guilin University of Aerospace Technology,Guilin 541004,Guangxi,China)

机构地区：[1]桂林理工大学信息科学与工程学院,广西桂林541006 [2]嵌入式技术与智能系统实验室,广西桂林541004 [3]可信软件重点实验室,广西桂林541004 [4]桂林航天工业学院电子信息与自动化学院,广西桂林541004

出　　处：《计算机应用与软件》2025年第2期330-335,354,共7页Computer Applications and Software

基　　金：国家自然科学基金项目(61802085,61862019,61563012);广西自然科学基金项目(2020GXNSFAA159038,2017GXNSFAA198223);广西可信软件重点实验室基金项目(kx202011)。

摘　　要：提出一种(γ,l-p,k)-匿名模型,模型引入了信息熵作为计算缺损数据的属性距离,通过敏感属性度高低分为不同的敏感级别,并设置相应的权重ω值,同时让等价类元组的不同敏感级别个数满足阈值γ。接着根据模型设计了加权信息熵匿名算法(Weighted Information Entropy Anonymous Algorithm based on Defect-Sensitive Attributes,WISA^(*))对缺损型数据集进行匿名化。实验结果表明,该算法不仅可以减少等价类信息损失,同时提高了敏感属性的多样性,从而降低了数据隐私泄露风险且复杂度较低。This paper proposes a(γ,l-p,k)-anonymity model.In the anonymous model,information entropy was introduced as the attribute distance to calculate the missing data,and the sensitive attribute degree was divided into different sensitive levels,and the corresponding weightωvalue was set.At the same time,we let the number of different sensitivity levels of equivalence class tuples meet the thresholdγ.According to the model,a weighted information entropy anonymity algorithm WISA^(*)was designed to anonymize the defective dataset.The experimental results show that the proposed algorithm WISA^(*)not only reduces the loss of equivalent information,but also improves the performance of sensitive attributes on diversity,thereby descending the risk of privacy leakage of the data with a low complexity.

关 键 词：信息熵 缺损数据 k -匿名 

分 类 号：TP319[自动化与计算机技术—计算机软件与理论]