Preserving Location Privacy of Connected Vehicles With Highly Accurate Location Updates

Abstract

Connected vehicles are at risk of exposing their location history when using potentially untrusted location-based services (LBSs) in the driving process. We propose a method called mutually obfuscating paths (MOP) that enables vehicles to provide highly accurate realtime location updates to LBS while preventing the LBS from tracking vehicles. The instrument is to leverage connected vehicles’ two network interfaces: in-car LTE Internet (for accessing LBS) and car-to-car Dedicated short-range communications (DSRC)-communication (for obfuscating their paths). The main idea of MOP is that vehicles, when appropriate, generate made-up but plausible location updates for each other, making their paths continuously branching off from the LBS’ viewpoint. We evaluations show that MOP provides strong privacy protection even under continuous and highly accurate location updates.