Reciprocal Cloaking Algorithm for Spatial K-Anonymity  

作　　者：侯士江 刘国华 

机构地区：[1]College of Information Science & Engineering,Yanshan University [2]School of Computer Science & Technology,Donghua University

出　　处：《Journal of Donghua University(English Edition)》2013年第1期49-53,共5页东华大学学报（英文版）

基　　金：National Natural Science Foundation of China(No.61070032)

摘　　要：Mobile devices with global positioning capabilities allow users to retrieve points of interest (POI) in their proximity. Due to the nature of spatial queries, location-based service (LBS) needs the user position in order to process requests. On the other hand, revealing exact user locations to LBS may pinpoint their identities and breach their privacy. Spatial K-anonymity (SKA) exploits the concept of K-anonymity in order to protect the identity of users from location-based attacks. However, existing reciprocal methods rely on a specialized data structure. In contrast, a reciprocal algorithm was proposed using existing spatial index on the user locations. At the same time, an adjusted median splits algorithm was provided. Finally, according to effectiveness (i.e., anonymizing spatial region size) and efficiency (i.e., construction cost), the experimental results verify that the proposed methods have better performance. Moreover, since using employ general-purpose spatial indices, the proposed method supports conventional spatial queries as well.Mobile devices with global positioning capabilities allow users to retrieve points of interest （POI） in their proximity. Due to the nature of spatial queries, location-based service （LBS） needs the user position in order to process requests. On the other hand, revealing exact user locations to LBS may pinpoint their identifies and breach their privacy. Spatial K-anonymity （SKA） exploits the concept of K-anonymity in order to protect the identity of users from location-based attacks. However, existing reciprocal methods rely on a specialized data structure. In contrast, a reciprocal algorithm was proposed using existing spatial index on the user locations. At the same time, an adjusted median splits algorithm was provided. Finally, according to etTectiveness （i. e., anonymizing spatial region size） and efficiency （i. e. , construction cost）, the experimental results verify that the proposed methods have better performance. Moreover, since using employ general.purpose spatial indices, the proposed method supports conventional spatial queries as well.

关 键 词：location-based services K-ANONYMITY PRIVACY spatial databases 

分 类 号：TP309.2[自动化与计算机技术—计算机系统结构]