A privacy-preserving method for publishing data with multiple sensitive attributes
作者机构：School of Computer Science and EngineeringGuangxi Normal UniversityGuilinChina School of Computer ScienceCommunication University of ChinaBeijingChina Department of Computer Science and MathematicsNipissing UniversityNorth BayOntarioCanada
出 版 物：《CAAI Transactions on Intelligence Technology》 (智能技术学报（英文）)
年 卷 期：2024年第9卷第1期
页 面：222-238页
核心收录：
学科分类：08[工学] 0839[工学-网络空间安全] 081201[工学-计算机系统结构] 0812[工学-计算机科学与技术（可授工学、理学学位）]
基 金：Doctoral research start-up fund of Guangxi Normal University Guangzhou Research Institute of Communication University of China Common Construction Project,Sunflower-the Aging Intelligent Community Guangxi project of improving Middle-aged/Young teachers'ability,Grant/Award Number:2020KY020323
主 题：data privacy data publishing
摘 要：The overgeneralisation may happen because most studies on data publishing for multiple sensitive attributes(SAs)have not considered the personalised privacy ***,sensitive information disclosure may also be caused by these personalised *** address the matter,this article develops a personalised data publishing method for multiple *** to the requirements of individuals,the new method partitions SAs values into two categories:private values and public values,and breaks the association between them for privacy *** the private values,this paper takes the process of anonymisation,while the public values are released without this *** algorithm is designed to achieve the privacy mode,where the selectivity is determined by the sensitive value frequency and undesirable *** experimental results show that the proposed method can provide more information utility when compared with previous *** theoretic analyses and experiments also indicate that the privacy can be guaranteed even though the public values are known to an *** overgeneralisation and privacy breach caused by the personalised requirement can be avoided by the new method.
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