随机匿名的位置隐私保护方法

Random anonymity method for location privacy protection

基于空间匿名区域的研究方法容易受到多查询攻击和推理攻击,从而带来隐私暴露问题。为了保证基于位置服务中的隐私安全,基于k-匿名思想,构建了随机k-隐藏集以满足位置k-匿名性和位置l-多样性。随机k-隐藏集是由离散的位置点组成,并且彼此之间的网格距离大于阈值s。利用私有信息检索协议保证了查询结果在检索过程中的隐私性,实现了服务提供者在无法知道用户精确查询结果的前提下为用户提供基于位置的服务。仿真实验验证了算法的安全性和有效性。

The methods that are based on the anonymous spatial region are vulnerable to multiple queries attacks and inference attacks,which result in the privacy exposure issues. In order to ensure the location-based privacy security,this paper constructed the random k-cloak set to meet requirement of location k-anonymity and location l-diversity. Random k-cloak set is composed of discrete dots of location,and the grid distance between dots is greater than the threshold value s. Private information retrieval employed in the study guaranteed privacy in retrieval processing,and achieved the goal that the server provides the location-based service for users on the premise of not knowing user＇s query results. Simulation experiments verify the security and validity of this method.