计算机工程与应用Issue(17)：18-23,37,7.DOI:10.3778/j.issn.1002-8331.1303-0277
基于k-频繁子图聚类的二分图匿名方法
Novel bipartite graph anonymous method based on k-frequent subgraph clustering
摘要
Abstract
In this paper, a novel bipartite graph anonymous method is proposed to against sensitive edges identification attacks from malicious users and to preserve the privacy of members in social networks. A positive one-way(c1, c2)-security, a negative one-way(c1, c2)-security, and a two-way(c1, c2)-security principles are introduced. These definitions are based on the k-security group theory, the sparsity of bipartite graphs, and the sensitive edges identification attacks in social networks. A bipartite graph anonymous problem is defined to against sensitive edges identification attacks. A bigraph partitioning algorithm is presented on the basis of k-frequent subgraphs clustering and a bipartite graph anonymous algorithm is given to assure the safety of the pub-lished bipartite graph. The experimental results show that under the equal time-cost conditions, the proposed method not only produces less information loss than that of the existing methods, but also effectively resists sensitive edges identification attacks and realizes security release of bipartite graphs.关键词
社会网络/隐私匿名/聚类/敏感边识别攻击/k-频繁子图Key words
social networks/privacy anonymity/clustering/sensitive edges identification attack/k-frequent subgraph分类
信息技术与安全科学引用本文复制引用
吴宏伟,张健沛,杨静..基于k-频繁子图聚类的二分图匿名方法[J].计算机工程与应用,2013,(17):18-23,37,7.基金项目
国家自然科学基金（No.61073043，No.61073041）；黑龙江省自然科学基金（No.F200901，No.G200827）；哈尔滨市科技创新人才研究专项资金（No.2011RFXXG015）；高等学校博士学科点专项科研基金（No.20112304110011，No.20122304110012）。 （）
