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多源数据关联访问控制模型下的隐私泄露定量分析

Privacy leakage quantitative analysis with multi⁃source data association access control model
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摘要 传统访问控制模型无法避免多源数据关联访问时的隐私泄露,量化多源数据之间关联性访问与隐私泄露的关系,可避免多源数据在交互式访问过程中隐私泄露。文中以π⁃演算的交互性与移动性理论为基础,形式化地分析多源数据之间的关联性访问控制模型,引入概率计算,提出一种隐私泄露定量分析新方法。该方法通过计算数据关联性的概率大小,并使用概率衡量隐私泄露的大小,从而动态地量化分析多源数据在交互式访问控制过程中的隐私泄露。仿真实验结果表明隐私泄露与多源数据关联性成正比关系。 The traditional access control model fails to avoid the privacy leakage during the multi⁃source data associated access,and quantify the relationship between the multi⁃source data association access and privacy leakage to avoid the privacy leakage of the multi⁃source data in the interactive access process.On the basis of the theory of interaction and mobility ofπ⁃calculus,the control model of association access among multi⁃source data is subjected to formalization analysis,the probability calculation is introduced,and a new method for quantitative analysis of privacy leakage is proposed.The probability of data relevance is calculated,and then the privacy leakage quantity is measured with the probability,so as to dynamically quantify and analyze the privacy leakage of multi⁃source data in the interactive access control process.The results of simulation experiment show that the privacy leakage is directly proportional to the relevance of multi⁃source data.
作者 吴福生 刘金会 倪明涛 李延斌 WU Fusheng;LIU Jinhui;NI Mingtao;LI Yanbin(Guizhou Key Laboratory of Big Data Statistical Analysis,Guizhou University of Finance and Economics,Guiyang 550025,China;Guizhou Key Laboratory of Economics System Simulation,Guizhou University of Finance and Economics,Guiyang 550025,China;School of Computer Science,Northwestern Polytechnical University,Xi’an 710129,China;School of Electronic Information and Artificial Intelligence,Leshan Normal University,Leshan 614000,China;College of Information Science and Technology,Nanjing Agricultural University,Nanjing 210095,China)
出处 《现代电子技术》 2022年第11期57-61,共5页 Modern Electronics Technique
基金 贵州省大数据统计分析重点实验室开放课题基金资助(BDSA20190105) 贵州省教育厅自然科学研究项目资助(黔教合KY字[2021]064) 国家自然科学基金项目资助(62062019) 国家自然科学基金项目资助(62061007) 国家自然科学基金项目资助(62072247)。
关键词 隐私泄露定量分析 多源数据关联访问 访问控制 π⁃演算 概率计算 大数据安全 privacy leakage quantitative analysis multi⁃source data association access access control π⁃calculus probability calculation big data security
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