%0 Journal Article
%T Preserving privacy in social networks based on d-neighborhood subgraph anonymity<br>基于d-邻域子图匿名的社会网络隐私保护*
%A JIN Hua
%A ZHANG Zhi-xiang
%A LIU Shan-cheng
%A JU Shi-guang
%A <br>金华
%A 张志祥
%A 刘善成
%A 鞠时光
%J 计算机应用研究
%D 2011
%I 
%X Preserving privacy is very necessary for social network information publishing, because analysis of social networks can violate the individual privacy. This paper proposed a k-anonymity model of d-neighborhood subgraph described by matrix of supe-edge. It transformed the anonymization of subgraph into matching the matrix which represented the d-neighborhood subgraph of vertex, and ensured that the numbers of isomorphic d-neighborhood subgraph was no less than k for every vertex. Experimental results show that the proposed model can effectively resist neighborhood attacks and preserve privacy information.
%K social networks
%K privacy preservation
%K d-neighborhood subgraph
%K k-anonymity<br>社会网络
%K 隐私保护
%K d-邻域子图
%K k-匿名
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=A9D9BE08CDC44144BE8B5685705D3AED&aid=1F8EB868F38CE07235BF75AF1724D7E5&yid=9377ED8094509821&vid=D3E34374A0D77D7F&iid=708DD6B15D2464E8&sid=6A1A591E8779B99D&eid=4308D94C89E52724&journal_id=1001-3695&journal_name=计算机应用研究&referenced_num=0&reference_num=11