A new anonymity model for privacy-preserving data publishing

摘要：

　　Privacy-preserving data publishing (PPDP) is one of the hot issues in the field of the network security.The existing PPDP technique cannot deal with generality attack,which explicitly contains sensitivity attack and similarity attack.This paper proposes a novel model,( w,y,k )-anonymity,to avoid generality attack.We show that the optimal ( w,y,k )-anonymity problem is NP-hard and conduct Top-down Local recoding (TDL) algorithm.Our experiments validate the improvement of our model with real data.

关键词： data publishing anonymity privacy protection data security

会议类型: 国内会议

会议名称: 第八届中国可信计算与信息安全学术会议

会议地点: 湖北恩施

会议语种:英文

页码: 1-10

在线出版日期: 2014-09-13（万方平台首次上网日期，不代表论文的发表时间）