%0 Journal Article
%T Social Networks Data Publication Based on k-anonymity<br>社会网络数据的k-匿名发布
%A LAN Li-hui
%A JU Shi-guang
%A JIN Hua
%A <br>兰丽辉
%A 鞠时光
%A 金华
%J 计算机科学
%D 2011
%I 
%X Because of scientific researching and data sharing, social networks data should be released. However, individual privacy will be breached if social networks data will be published directly. Therefore, privacy protection should be carried on while releasing social networks data. A privacy protection method based on k-anonymity was proposed. The method is suitable for the scene that the aggressor with background knowledge of neighborhood information wants to reidentify the target node in published social networks. According to the individual privacy protection rectuirement, the entities set different levels of privacy protection to share data and improve data utility as possible as. Designed and implemented the KNP algorithm to publish data anonymously and carry on experiment on dataset to validate the algorithm. Experimental results show that the algorithm can effectively resist the neighborhood attack.
%K Social networks
%K Privacy protection
%K k-anonymity
%K Neighborhood attack<br>社会网络，隐私保护，k-匿名，邻域攻击
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=64A12D73428C8B8DBFB978D04DFEB3C1&aid=17DDCED190714E79F6FC6857A8AF9EF7&yid=9377ED8094509821&vid=16D8618C6164A3ED&iid=708DD6B15D2464E8&sid=3F0AF5EDBC960DB0&eid=1B97AE5098AEB49C&journal_id=1002-137X&journal_name=计算机科学&referenced_num=0&reference_num=0