基于边分割的社交网络敏感边保护技术  

Edge partitioning approach for protecting sensitive relationships in social network

作　　者：范国婷[1,2] 罗永龙[1,2] 孙丹丹[1,2] 王涛春[1,2] 郑孝遥[1,2] 

机构地区：[1]安徽师范大学数学计算机科学学院,安徽芜湖241003 [2]安徽师范大学网络与信息安全工程技术研究中心,安徽芜湖241003

出　　处：《计算机应用》2016年第1期207-211,221,共6页journal of Computer Applications

基　　金：国家自然科学基金资助项目(61370050;61402014);安徽省自然科学基金资助项目(1308085QF118)~~

摘　　要：用户间的敏感关系是社交网络中用户的重要隐私信息。为了解决社交网络中用户间敏感关系泄露问题,提出一种边分割算法。首先,将已删除敏感边的简单匿名社交网络的非敏感边分割成多条子边;然后,将原非敏感边携带的信息分配到子边上,使得每条子边只携带原非敏感边的部分信息,从而生成具有隐私能力的匿名社交网络。理论分析和仿真实验结果表明,相比cluster-edge和cluster-based with constraints算法,边分割算法在保证数据具有较高可用性的情况下能更大限度降低敏感关系泄露的概率,泄露概率分别降低了约30%和20%,因此所提算法能够有效解决社交网络中敏感关系泄露问题。The sensitive relationships between users are important privacy information in social networks. Focusing on the issue of sensitive relationships leakage between users, an edge partitioning algorithm was proposed. Firstly, every nonsensitive edge was partitioned into some sub-edges after the sensitive edge was deleted in social networks. Secondly, every sub-edge was assigned information which belongs to the original non-sensitive edge. So every sub-edge contained part information of the original non-sensitive edge. The anonymized social network that preserves privacy was generated finally. In the comparison experiments with cluster-edge algorithm and cluster-based with constraints algorithm, the edge partitioning algorithm had a greater decrease of the probability of sensitive relationships leakage with maintaining high availability of data.The probability was decreased by about 30% and 20% respectively. As a result, the edge partitioning algorithm can effectively protect sensitive relationships in social networks.

关 键 词：社交网络 隐私保护 敏感边 分割 匿名 

分 类 号：TP309.2[自动化与计算机技术—计算机系统结构]