电子学报2016，Vol.44Issue(6)：1437-1444,8.DOI:10.3969/j.issn.0372-2112.2016.06.026
基于k-度匿名的社会网络隐私保护方法
Privacy Preservation Method Based on k-Degree Anonymity in SociaI Networks
摘要
Abstract
To preserve the privacy of social networks,most existing methods are applied to satisfy different anonymity models,but some serious problems are involved such as often incurring large information losses and great structural modifi-cations of original social network after being anonymized.Therefore,an improved privacy protection model called Similar-Graph is proposed,which is based on k-degree anonymous graph derived from k-anonymity to keep the network structure sta-ble.Where the main idea of this model is firstly to partition network nodes into optimal number of clusters according to de-gree sequences based on dynamic programming,and then to reconstruct the network by means of moving edges to achieve k-degree anonymity with internal relations of nodes considered.To differentiate from traditional data disturbing or graph modif-ying method used by adding and deleting nodes or edges randomly,the superiority of our proposed scheme lies in which nei-ther increases the number of nodes and edges in network,nor breaks the connectivity and relational structures of original net-work.Experimental results show that our SimilarGraph model can not only effectively improve the defense capability against malicious attacks based on node degrees,but also maintain stability of network structure.In addition,the cost of information losses due to anonymity is minimized ideally.关键词
社会网络/隐私保护/k-度匿名/信息损失Key words
social network/privacy preservation/k-degree anonymity/information loss分类
信息技术与安全科学引用本文复制引用
龚卫华,兰雪锋,裴小兵,杨良怀..基于k-度匿名的社会网络隐私保护方法[J].电子学报,2016,44(6):1437-1444,8.基金项目
浙江省自然科学基金（No．LY13F020026，No．Y1080102，No．LY14F020017，No．LY14C130005）；国家自然科学基金（No．61571400，No．61070042）；中国博士后科学基金（No．2015M581957）；浙江省博士后科研项目择优资助 （）
