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基于边介数模型的差分隐私保护方案 被引量:7

Differential privacy protection scheme based on edge betweenness model
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摘要 随着社交网络应用的不断发展,用户社交关系等个人隐私数据的安全保护问题亟待解决。为显著减小社交网络数据的敏感度,提出了一种基于边介数模型的差分隐私保护方案BCPA。基于dK模型捕获图结构对应的2K序列,根据边中介中心性系数对2K序列重新排序;依据排序结果将2K序列聚类成多个子序列,再利用dK扰动算法对各子序列分别进行加噪;根据整合后的新2K序列生成满足差分隐私的社交网络发布图。基于真实数据集,通过模拟仿真将所提方案与其他经典方案进行比较,实验结果表明,所提方案在保证较强隐私保护性的同时,提高了发布数据的准确性和可用性。 With the continuous development of social network application, user’s personal social data is so sensitive that the problem of privacy protection needs to be solved urgently. In order to reduce the network data sensitivity, a differen- tial privacy protection scheme BCPA based on edge betweenness model was proposed. The 2K sequence corresponding to the graph structure based on the dK model was captured, and 2K sequences based on the edge betweenness centrality were reordered. According to the result of reordering, the 2K sequence was grouped into several sub-sequences, and each sub-sequence was respectively added with noise by a dK perturbation algorithm. Finally, a social network graph satisfy- ing differential privacy was generated according to the new 2K sequences after integration. Based on the real datasets, the scheme was compared with the classical schemes through simulation experiments. The results demonstrate that it im- proves the accuracy and usability of data while ensuring desired privacy protection level.
作者 黄海平 王凯 汤雄 张东军 HUANG Haiping;WANG Kai;TANG Xiong;ZHANG Dongjun(College of Computer, Nanjing University of Posts and Telecommunications, Nanjing 210023, China;High Technology Research Key Laboratory of Wireless Sensor Network of Jiangsu Province, Nanjing 210023, China)
出处 《通信学报》 EI CSCD 北大核心 2019年第5期88-97,共10页 Journal on Communications
基金 国家自然科学基金资助项目(No.61672297) 江苏省重点研发计划(社会发展)基金资助项目(No.BE2017742) 江苏省六大人才高峰基金资助项目(No.DZXX-017)~~
关键词 社交网络 隐私保护 差分隐私 dK 模型 聚类 分组扰动 social network privacy protection differential privacy dK model clustering group perturbation
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