基于边介数模型的差分隐私保护方案

doi:10.11959/j.issn.1000-436x.2019095

Abstract

Abstract:

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 differential 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 satisfying 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 improves the accuracy and usability of data while ensuring desired privacy protection level.

Key words: social network, privacy protection, differential privacy, dK model, clustering, group perturbation

CLC Number:

TP309

Haiping HUANG,Kai WANG,Xiong TANG,Dongjun ZHANG. Differential privacy protection scheme based on edge betweenness model[J]. Journal on Communications, 2019, 40(5): 88-97.

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Differential privacy protection scheme based on edge betweenness model

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