公路网移动用户隐私保护算法研究*

移动商务1,2]中的隐私保护3,4]是实际应用中要解决的关键问题之一，而基于位置的移动隐私保护算法可以提供精确查询结果同时保护个人隐私信息。为移动用户定义个性化隐私配置文件，建立KLP匿名模型，并基于其提出一种通过匿名集交换合并过程实现的隐私保护算法（AMAGS）。算法是一个合并交换的过程，具有最小化初始K匿名集的特点。AMAGS可以用来保护公路网5,6]移动用户的位置、身份以及其他敏感信息。通过仿真实验表明，AMAGS可以在有效保护数据隐私的前提下，花费比P3RN更少的查询时间和更低的查询成本，得到更加精确的查询结果。

Research on privacy protection algorithm for mobile users of road network*

Privacy-preserving is one of the key issues to be solved in practical applications, while location-based mobile privacy protection provides accurate query results while protecting personal privacy information. In order to define personalized privacy profiles for mobile users, a KLP anonymous model is built, and a privacy protection algorithm (AMAGS) based on anonymous set exchange merging process is proposed, which features the construction of minimal initial K-anonymity sets, an exchanging process and a merging process. The algorithm can be used to protect the location, identifier and other sensitive information of the mobile users on a road network. The simulation results show that AMAGS can obtain more accurate results with less response time and lower query cost than P3RN under the premise of effectively protecting data privacy.