The Community for Technology Leaders
Green Image
Issue No. 03 - June (2018 vol. 26)
ISSN: 1063-6692
pp: 1123-1136
Gang Wang , Department of Computer Science, Virginia Tech, Blacksburg, VA, USA
Bolun Wang , Department of Computer Science, University of California at Santa Barbara, Santa Barbara, CA, USA
Tianyi Wang , ByteDance Inc., Beijing, China
Ana Nika , Department of Computer Science, University of California at Santa Barbara, Santa Barbara, CA, USA
Haitao Zheng , Department Computer Science, University of California at Santa Barbara, Santa Barbara, CA, USA
Ben Y. Zhao , Department Computer Science, University of California at Santa Barbara, Santa Barbara, CA, USA
ABSTRACT
Real-time crowdsourced maps, such as Waze provide timely updates on traffic, congestion, accidents, and points of interest. In this paper, we demonstrate how lack of strong location authentication allows creation of software-based Sybil devices that expose crowdsourced 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 precise movements 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 co-location of a pair of devices. Over time, co-location edges combine 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 their system.
INDEX TERMS
Global Positioning System, Accidents, Mobile handsets, Privacy, Google, Roads, Real-time systems
CITATION

G. Wang, B. Wang, T. Wang, A. Nika, H. Zheng and B. Y. Zhao, "Ghost Riders: Sybil Attacks on Crowdsourced Mobile Mapping Services," in IEEE/ACM Transactions on Networking, vol. 26, no. 3, pp. 1123-1136, 2018.
doi:10.1109/TNET.2018.2818073
232 ms
(Ver 3.3 (11022016))