位置轨迹隐私保护综述

Review on Location Trajectory Privacy Protection

基于位置服务在为用户的日常生活带来极大便利的同时,又不可避免地导致一定程度上用户隐私信息的泄露。在隐私泄露问题上,当前较为关注的是用户在使用位置服务时位置隐私的泄露。大量的位置数据存在着相互关联进而有形成位置轨迹的可能,而位置轨迹数据含有比单纯的位置数据更为丰富的时空关联,这些关联使得攻击者更容易获取用户的隐私信息。针对这一问题,研究者们提出了大量针对位置轨迹数据的隐私保护方法。在众多的位置轨迹隐私保护方法中,如何找到同类方法,有针对性地进行位置轨迹隐私保护研究成为研究者不得不面对的问题。文章在借鉴已有分类方法的基础上,针对近年来提出的和由原有算法改进而来的位置轨迹隐私保护算法,基于攻击者所掌握的背景知识,从位置轨迹追踪和位置轨迹重构两种攻击方法的角度对这些算法加以分类,总结并分析其优缺点。最后,文章针对当前潜在的数据挖掘攻击技术,提出了研究展望。

Location based service brings great convenience for users in daily life, but at the same time it inevitably leads to a certain degree of users＇ private information exposure. On issues of privacy, the focus of current research is protection of users＇ location privacy. Due to the relationships between locations, scattered locations could be constituted into location trajectory, and that location trajectory contains more spatio-temporal correlations, with comparison of solo location. The attacker could be more accessible to user＇s privacy with the help of these correlations. In order to solve this problem, researchers put forward a lot of methods to protect the location trajectory privacy. But how to find the similar methods for study or imitation has puzzled the researcher, because there is no specific classification. In this article, based on the attack techniques of location trajectory tracking and reconstruction, we propose a new classification. With this classification, we analyze these protection methods and summarize the advantages and disadvantages of them. Finally, we put forward in the research prospects for the potential attacks of data mining technology.