Provable and Practical Location Privacy for Vehicular and Mobile Systems
Raluca Ada Popa · 2010
In recent years, there has been a rapid evolution of location-based vehicular and mobile services (e.g., electronic tolling, congestion pricing, traffic statistics, insurance pricing, locationbased social applications), which promise tremendous benefits to users. Unfortunately, most such systems pose a serious threat to the location privacy of users because they track each individual’s path. A question that arises naturally is how can we preserve location privacy of users while maintaining the benefits of such services? In this thesis, we address this question by tackling two general problems that are the foundation of many of the aforementioned services. The first problem is how to enable an untrusted server to compute agreed-upon functions on a specific user’s path without learning the user’s path. We address this problem in a system called VPriv. VPriv supports a variety of applications including electronic tolling,