中文摘要：

针对移动社交网络迅猛发展带来的发布轨迹隐私泄露问题,提出了一种个性化的轨迹保护方案。根据个体个性化的隐私保护需求差异,对不同个体采用了不同的保护准则,这样可以解决传统隐私保护下过度保护及轨迹效用低等问题。给出k敏感轨迹匿名和（k,p）敏感轨迹匿名等重要的隐私保护定义,并利用Trie树的构造、剪枝、重构等技术实现了个体的个性化隐私保护。通过在真实数据集上的实验分析,证明该个性化方案比现存隐私保护方案在轨迹位置损失率方面性能更优,计算延时较低且效率更高。

英文摘要：

With the dramatic development of mobile social networks,trajectory publishing privacy-preserving problem is getting increasingly concerned. To address this problem,this paper proposed a personalized trajectory privacy-preserving scheme.This scheme adopted different criteria which were based on the different demands of personalized privacy-preserving. This scheme could solve the problem of overprotection and low trajectory utility. It stated several different privacy-preserving definitions： k sensitive trajectory anonymity,（ k,p） sensitive trajectory anonymity,etc. This scheme was based on some technologies on Tire tree,including construction,pruning and reconstruction. Finally,it evaluated this scheme on real-world dataset,the experiment results show that our scheme is better in trajectory location loss ratio and more efficient than state-of-the-art for privacy-preserving.