内蒙古科技大学 机构 信息工程学院,内蒙古,包头,014000
纸质出版:2017
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张文超, 张晓琳, 张臣, 刘立新, 何晓玉. 分布式个性化社会网络隐私保护方法[J]. 微电子学与计算机, 2017, 34(6): 72-77, 83.
ZHANG Wen-chao, ZHANG Xiao-lin, ZHANG Chen, et al. Distributed Personalized Social Privacy Protection Method[J]. 2017, 34(6): 72-77.
提出了一种基于图结构扰乱的分布式个性化社会网络隐私保护方法DP-GSPerturb(Distributed personalized graph structure perturbation).该方法在分布式环境下
以节点为中心
通过节点间消息传递和节点值更新
查找敏感源节点的可达节点
传递可达信息给敏感源节点
随机扰乱敏感源节点的连接关系
实现敏感连接关系的个性化隐私保护.实验结果表明
DP-GSPerturb方法提高了处理大规模社会网络图数据的效率和数据发布的可用性.
DP-GSPerturb is a distributed personalized social privacy protection method based on graph structure perturbation; it is proposed to solve sensitive link privacy issues in personalized social networks. The method is a node-centric method that searches reachable nodes of sensitive source nodes
transfers reachable information to sensitive source nodes
and randomly perturbs links of sensitive source nodes through between-node messaging
node value updating to achieve the personalized privacy protection of sensitive link in the distributed environment. The experimental results show that DP-GSPerturb improves not only the processing speed of large-scale graph data but also the availability of data published.
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