Abstract
Privacy preservation has recently received considerable attention in location-based services (LBSs). A large number of location cloaking algorithms have been proposed for protecting the location privacy of mobile users. However, most existing cloaking approaches assume that mobile users are trusted. And exact locations are required to protect location privacy, which is exactly the information mobile users want to hide. In this paper, we propose a p-anti-conspiration privacy model to anonymize over semi-honest users. Furthermore, two k*NNG-based cloaking algorithms, vk*NNCA and ek*NNCA, are proposed to protect location privacy without exact locations. The efficiency and effectiveness of the proposed algorithms are validated by a series of carefully designed experiments. The experimental results show that the price paid for location privacy protection without exact locations is small.
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Xiao PAN is a lecturer at Shijiazhuang Tiedao University, and a member of the Soft Science Research Institute on Engineering and Construction Management in Hebei province. She received her PhD in Computer Science from Renmin University of China in 2010. Her research interests include data management on moving objects and location privacy protection.
Xiaofeng Meng is a professor in the School of Information, Renmin University of China. He received his BS in 1987 from Hebei University, the MS in 1993 from Renmin University of China, and PhD in 1999 from the Institute of Computing Technology, Chinese Academy of Sciences, all in Computer Science. His research interests include mobile data management, Web data integration, native XML databases, and flash-based databases. He is the secretary general of the Database Society of the China Computer Federation (CCF DBS). He has published more than 100 technical papers in refereed international journals and conference proceedings.
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Pan, X., Meng, X. Preserving location privacy without exact locations in mobile services. Front. Comput. Sci. 7, 317–340 (2013). https://doi.org/10.1007/s11704-013-2020-y
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DOI: https://doi.org/10.1007/s11704-013-2020-y