一种基于兴趣点分布的匿名框KNN查询方法  

A Privacy-Preserving Method Based on Po Is Distribution Using Cloaking Region for K Nearest Neighbor Query

作　　者：朱顺痣[1] 黄亮[2] 周长利[3] 马樱[1] 

机构地区：[1]厦门理工学院计算机与信息工程学院,福建厦门361024 [2]国家计算机网络应急技术处理协调中心,北京100029 [3]华侨大学计算机科学与技术学院,福建厦门361021

出　　处：《电子学报》2016年第10期2423-2431,共9页Acta Electronica Sinica

基　　金：国家自然科学基金(No.61373147;No.61502404);福建省自然科学基金(No.2016Y0079;No.2015J05132);福建省教育厅A类项目(No.JA14234)

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.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.

关 键 词：位置隐私 基于位置的服务 匿名框 K近邻查询 

分 类 号：TP311[自动化与计算机技术—计算机软件与理论]