Location Privacy-Preserving Method for LBS Continuous KNN Query in Road Networks
-
摘要: 位置隐私保护与基于位置的服务(location based service, LBS)的查询服务质量是一对矛盾，在连续查询(continuous query)和实际路网环境下，位置隐私保护问题需考虑更多限制因素.如何在路网连续查询过程中有效保护用户位置隐私的同时获取精确的兴趣点(place of interest, POI)查询结果是目前的研究热点.利用假位置的思想，提出了路网环境下以交叉路口作为锚点的连续查询算法，在保护位置隐私的同时获取精确的K邻近查询(K nearest neighbor, KNN)结果；基于注入假查询和构造查询匿名组的方法，提出了抗查询内容关联攻击和抗运动模式推断攻击的轨迹隐私保护方法，并在分析中给出了位置隐私保护和查询服务质量平衡方法的讨论.性能分析及实验表明，该方法能够在连续查询中提供较强的位置隐私保护，并具有良好的实效性和均衡的数据通信量.Abstract: Location privacy preservation and query service quality are a pair of contradiction in location based service (LBS). In the road network, there are a lot of limiting factors to be considered for continuous query. How to protect location privacy efficiently and acquire accurate continuous query results of places of interest (POIs) are great challenges in the road network. In this paper, based on the idea of using fake location, a query algorithm is proposed firstly, which picks the intersections of the road network gradually to form an anchor sequence to query POIs, and the query algorithm can not only achieve location privacy preservation but also deduce accurate K nearest neighbor (KNN) query results. And then, based on the idea of sending fake queries and constructing query anonymity group, a trajectory privacy preservation algorithm is proposed, which is used to resist continuous query correlation attack and movement model inference attack. At last, a discussion about the trade-off between privacy preservation and query service quality is given in the road networking LBS. The performance analysis and experiments show that our methods provide strong location privacy preservation and get accurate query results in the road network, and our algorithms have favorable timeliness and well-balanced data communication overhead.
-
计量
- 文章访问数: 1439
- HTML全文浏览量: 2
- PDF下载量: 899
下载:
