基于缓存候选结果集的轨迹隐私保护方法  

A Trajectory Privacy Preserving Method Based on Caching Candidate Result Set

作　　者：张少波[1] 刘琴 李雄[1] 王国军[3] ZHANG Shao-bo;LIU Qin;LI Xiong;and WANG Guo-jun(School of Computer Science and Engineering, Hunan University of Science and Technology Xiangtan Hunan 411201;College of of Computer Science and Electronic Engineering, Hunan University Changsha 410082;School of Computer Science and Educational Software, Guangzhou University Guangzhou 510006)

机构地区：[1]湖南科技大学计算机科学与工程学院,湖南湘潭411201 [2]湖南大学信息科学与工程学院,长沙410082 [3]广州大学计算机科学与教育软件学院,广州510006

出　　处：《电子科技大学学报》2018年第3期449-454,共6页Journal of University of Electronic Science and Technology of China

基　　金：国家自然科学基金(61632009;61402161;61300220;61772194);湖南省自然科学基金(2015JJ3046);湖南省教育厅资助科研项目(16B089)

摘　　要：在基于位置服务的连续范围查询过程中,针对相交区域需要重复查询的问题,提出一种基于缓存候选结果集的轨迹隐私保护方法。该方法采用二级缓存机制,分别在用户端和匿名器中缓存用户查询得到的候选结果集,供用户移动轨迹上的后续查询点使用,以减少用户与服务器之间的交互,降低用户信息暴露给服务器的风险。同时通过基于Markov模型的移动位置预测方法进行k-匿名,提高缓存的命中率。安全分析表明该方法能有效保护用户的轨迹隐私。实验结果显示该方法能减小服务器的计算和通信开销。To address the intersecting region of the continuous range queries needs to repeat queries in the location-based service, this paper proposes a method of trajectory privacy protection based on caching candidate result set. The method utilizes two-level cache mechanism to cache user＇s candidate result set at client and anonymizer, and the next query point on the trajectory can obtain the answer from the cached data, which can reduce the interaction between the user and the server to reduce the risk of user＇s information exposed to the server. At the same time, we propose the k-anonymity of the mobile location prediction based on the Markov model, which can improve the hit ratio of cache and enhance the user＇s trajectory privacy. Security analysis shows that the method can effectively protect the user＇s trajectory privacy. Experiments show this method can reduce the computation and communication overhead of the server.

关 键 词：缓存 K-匿名 基于位置服务 MARKOV模型 轨迹隐私 

分 类 号：TP309[自动化与计算机技术—计算机系统结构]