D-VSSP:分布式社会网络隐私保护算法

摘要

The processing efficiency of traditional social network privacy preserving technology for large-scale social network data is low.To solve this problem,a distributed vertex splitting social network privacy preserving(D-VSSP) algorithm was proposed.D-VSSP algorithm deals the large-scale social network data in parallel with MapReduce compuring model and Pregel-like model.Firstly,using MapReduce distributed model processes the vertex labels with methodof label triyialization,grouping trivialized label and exact grouping.And then it realizes distributed vertex splitting anonymity based on the message passing mechanisms of Pregel-like through splitting vertex electing.The experimental results show that the D-VSSP algorithm is superior to the traditional algorithm in processing efficiency for large-scale social network data.%针对传统社会网络隐私保护技术对大规模社会网络数据处理效率较低的问题,提出一种分布式结点分裂匿名社会网络隐私保护算法(Distributed-Vertex Splitting Social Network Privacy Preserving,D-VSSP).D-VSSP算法利用MapReduce和Pregel-like分布式计算模型处理社会网络图数据.首先基于MapReduce分布式计算模型对大图中的结点的标签信息进行标签平凡化、标签平凡化分组和精确分组处理;然后基于Pregel-like的消息传递机制,选举结点分裂,进行分布式结点分裂匿名.实验结果表明,在对大规模社会网络数据的处理效率上,D-VSSP算法优于传统算法.