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Issue No. 01 - Jan. (2014 vol. 13)
ISSN: 1536-1233
pp: 159-173
Krishna P. N. Puttaswamy , Dept. of Comput. Sci., Univ. of California, Santa Barbara, Santa Barbara, CA, USA
Shiyuan Wang , Dept. of Comput. Sci., Univ. of California, Santa Barbara, Santa Barbara, CA, USA
Troy Steinbauer , Dept. of Comput. Sci., Univ. of California, Santa Barbara, Santa Barbara, CA, USA
Divyakant Agrawal , Dept. of Comput. Sci., Univ. of California, Santa Barbara, Santa Barbara, CA, USA
Amr El Abbadi , Dept. of Comput. Sci., Univ. of California, Santa Barbara, Santa Barbara, CA, USA
Christopher Kruegel , Dept. of Comput. Sci., Univ. of California, Santa Barbara, Santa Barbara, CA, USA
Ben Y. Zhao , Dept. of Comput. Sci., Univ. of California, Santa Barbara, Santa Barbara, CA, USA
ABSTRACT
Using geosocial applications, such as FourSquare, millions of people interact with their surroundings through their friends and their recommendations. Without adequate privacy protection, however, these systems can be easily misused, for example, to track users or target them for home invasion. In this paper, we introduce LocX, a novel alternative that provides significantly improved location privacy without adding uncertainty into query results or relying on strong assumptions about server security. Our key insight is to apply secure user-specific, distance-preserving coordinate transformations to all location data shared with the server. The friends of a user share this user's secrets so they can apply the same transformation. This allows all location queries to be evaluated correctly by the server, but our privacy mechanisms guarantee that servers are unable to see or infer the actual location data from the transformed data or from the data access. We show that LocX provides privacy even against a powerful adversary model, and we use prototype measurements to show that it provides privacy with very little performance overhead, making it suitable for today's mobile devices.
INDEX TERMS
Servers, Privacy, Indexes, Cryptography, Data privacy, Transforms, Mobile computing,location transformation, Servers, Privacy, Indexes, Cryptography, Data privacy, Transforms, Mobile computing, efficiency, Location privacy, security, location-based social applications
CITATION
Krishna P. N. Puttaswamy, Shiyuan Wang, Troy Steinbauer, Divyakant Agrawal, Amr El Abbadi, Christopher Kruegel, Ben Y. Zhao, "Preserving Location Privacy in Geosocial Applications", IEEE Transactions on Mobile Computing, vol. 13, no. , pp. 159-173, Jan. 2014, doi:10.1109/TMC.2012.247
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