基于连续近邻服务请求的位置匿名方法的研究

Research on dummy-based location privacy protection for continuous proximity requests

为了使用户在使用基于位置的服务时,用户的位置信息不被泄露,国内外学者提出很多种解决方案,其中一种典型的方法是冗余地址查询方法。然而之前的方法在连续的近邻查询过程中存在处理速度较慢,反应延迟较大的问题。为了提高冗余匿名方法连续近邻查询的查询速度和效率,利用局部性原理,提出了一种改进算法,能够有效提高服务器的处理速度和查询时间,减少响应延迟。实验结果表明,对连续性较强的近邻查询,该方法相对于之前的方法查询性能有较大的提高。

Due to user＇s privacy threat increased in location based services （LBSs）, various location privacy-preserving Mechanisms have been proposed in the literature to address the privacy risks derived from the exposure of user locations through the use of LBSs. One of typical anonymization methods is dummy-based approach. However, previous approaches have the slow server processing and long delay. This paper proposed an improved algorithm based on temporal locality for continuous proximity requests, instead of updating proximity relationship with repetitive computation. It could effectively improve the processing speed, reduce the response delay. An empirical study shows that the new algorithm has obvious advantages in efficiency compared, with traditional dummy-based approach for continuous location-based proximity query requests.