Preserving location privacy in geosocial applications
Krishna P. N. Puttaswamy
Shiyuan Wang
Troy Steinbauer
Divyakant Agrawal
Amr El Abbadi
Chris Kruegel
Ben Y. Zhao
IEEE Transactions on Mobile Computing (TMC 2014)
[Full Text in PDF Format, 1.07 MB]
Paper 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.