Ghost Riders: A New Approach based on Co-Location Edges

Abstract

Real-time crowdsourced maps, suchas Waze provide timely updates on traffic, congestion, accidents, and points of interest. Inthis paper, we demonstrate how lack of strong location authentication allows creation of software-based Sybil devices that exposecrowdsourced map systems to a variety of security and privacy attacks. Our experiments show that a single Sybil device with limited resources can cause havoc on Waze, reporting false congestion and accidents and automatically rerouting user traffic. More importantly, we describe techniques to generate Sybil devices at scale, creating armies of virtual vehicles capable of remotely tracking precisemovements for large user populations while avoiding detection. To defend against Sybil devices, we propose a new approach based on co-location edges, authenticated records that attest to the one-time physical colocation of apair of devices. Over time, co-location edgescombine to form large proximity graphs that attest to physical interactions between devices, allowing scalable detection of virtual vehicles. We demonstrate the efficacy of this approach using large-scale simulations, and how they can be used to dramatically reduce the impact of the attacks. We have informed Waze/Google team of our research findings. Currently, we are in active collaboration with Waze team to improve the security and privacy of theirsystem.