Cloaking locations for anonymous location based services: a hybrid approach

An important privacy issue in Location Based Services is to hide a user’s identity while still provide quality location based services. Previous work has addressed the problem of locational -anonymity either based on centralized or decentralized schemes. However, a centralized scheme relies on an anonymizing server (AS) for location cloaking, which may become the performance bottleneck when there are large number of clients. More importantly, holding information in a centralized place is more vulnerable to malicious attacks. A decentralized scheme depends on peer communication to cloak locations and is more scalable. However, it may pose too much computation and communication overhead to the clients. The service fulfillment rate may also be unsatisfied especially when there are not enough peers nearby. This paper proposes a new hybrid framework called HiSC that balances the load between the AS and mobile clients. HiSC partitions the space into base cells and a mobile client claims a surrounding area consisting of base cells. The number of mobile clients in the surrounding cells is kept and updated at both client and AS sides. A mobile client can either request cloaking service from the centralized AS or use a peer-to-peer approach for spatial cloaking based on personalized privacy, response time, and service quality requirements. HiSC can elegantly distribute the work load between the AS and the mobile clients by tuning one system parameter base cell size and two client parameters - surrounding cell size and tolerance count. By integrating salient features of two schemes, HiSC successfully preserves query anonymity and provides more scalable and consistent service. Both the AS and the clients can enjoy much less work load. Additionally, we propose a simple yet effective random range shifting algorithm to prevent possible privacy leakage that would exist in the original P2P approach. Our experiments show that HiSC can elegantly balance the work load based on privacy requirements and client distribution. HiSC provides close to optimal service quality. Meanwhile, it reduces the response time by more than an order of magnitude from both the P2P scheme and the centralized scheme when anonymity level(value of ) or number of clients is large. It also reduces the update message cost of the AS by nearly 6 times and the peer searching message cost of the clients by more than an order of magnitude.

Chengyang ZhangEmail:

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Chengyang Zhang   received his B.S. degree in Industrial Automation from University of Science and Technology, Beijing in 2000 and master degree in computer system engineering from University of Science and Technology, Beijing in 2003. He is currently a Ph.D. student at the Computer Science and Engineering department of University of North Texas, Denton, TX, USA. His research interests include location based services, spatio-temporal databases, and geo-stream data management systems. Yan Huang   received her B.S. degree in Computer Science from Beijing University, Beijing, China, in July 1997 and Ph.D. degree in Computer Science from University of Minnesota, Twin-cities, MN, USA, in July 2003. She is currently an assistant professor at the Computer Science and Engineering Department of University of North Texas, Denton, TX, USA. Her research interests include geo-sensor networks, spatial databases, and data mining. She is a member of the IEEE Computer Society, the ACM, and the ACM SIGMOD. Her research is supported by Texas Advanced Research Program (ARP), Oak Ridge National Lab, and NSF.