Position transformation: a location privacy protection method for moving objects

Abstract

The expanding use of location-based services has profound implications on the privacy of personal information. In this paper, we propose a framework for preserving location privacy based on the idea of sending to the service provider suitably modified location information. Agents execute data transformation and the service provider directly processes the transformed dataset. Our technique not only prevents the service provider from knowing the exact locations of users, but also protects information about user movements and locations from being disclosed to other users who are not authorized to access this information. We also define a privacy model to analyze our framework, and examine our approach experimentally.