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ECWAY TECHNOLOGIES
IEEE PROJECTS & SOFTWARE DEVELOPMENTS
OUR OFFICES @ CHENNAI / TRICHY / KARUR / ERODE / MADURAI / SALEM / COIMBATORE
BANGALORE / HYDRABAD
CELL: 9894917187, 875487 1111/2222/3333/8754872111 / 3111 / 4111 / 5111 / 6111 / 8111
Visit: www.ecwayprojects.com Mail to: ecwaytechnologies@gmail.com

PRESERVING LOCATION PRIVACY IN GEOSOCIAL APPLICATIONS

ABSTRACT:
Using geosocial applications, such as Four Square, 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.

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Preserving location privacy in geosocial applications

  • 1. ECWAY TECHNOLOGIES IEEE PROJECTS & SOFTWARE DEVELOPMENTS OUR OFFICES @ CHENNAI / TRICHY / KARUR / ERODE / MADURAI / SALEM / COIMBATORE BANGALORE / HYDRABAD CELL: 9894917187, 875487 1111/2222/3333/8754872111 / 3111 / 4111 / 5111 / 6111 / 8111 Visit: www.ecwayprojects.com Mail to: ecwaytechnologies@gmail.com PRESERVING LOCATION PRIVACY IN GEOSOCIAL APPLICATIONS ABSTRACT: Using geosocial applications, such as Four Square, 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.