中文摘要：

针对利用匿名框实现的兴趣点K近邻（KNN）查询带来的通信开销大、时延长等问题,提出了基于单一兴趣点Voronoi图划分和四叉树层次化组织的KNN查询方法.该方法根据兴趣点层次信息有针对性的构造查询匿名框用来获取详细查询信息,在保护位置隐私的同时,降低了查询通信开销,同时注入虚假查询保护了用户的真实查询内容隐私.最后分别采用模拟地理数据和真实地理数据进行理论分析和有效性验证.

英文摘要：

Achieving KNN query with traditional cloaking region brings higher communication cost and delay caused by useless points of interest（ Po I） returned,a newKNN query method is proposed. Based on Voronoi diagram division of Po Is and hierarchical index quadtree structure,cloaking region can be constructed purposefully. Due to the targeted query request,the communication cost is decreasing compared with traditional cloaking region methods. And injecting fake query requests makes the query content privacy preserving work. We have verified the effectiveness of our proposal by analysis and experiments.