Security of Connected Vehicles



Vehicular networks present tremendous opportunities to increase safety through applications such as collision avoidance or traffic and congestion control by means of vehicle-to-vehicle and vehicle-to-infrastructure communication. They also present opportunities to increase the user experience through emerging applications such as entertainment, mobile Internet games, mobile shopping, etc, applications facilitated by the future self-driven cars.

In order to ensure the successful adoption of these applications connected vehicles networks have to address the same major concerns that all form of communications have in terms of security, from bootstrapping trust to ensuring authentication and integrity of the communication, to more complex issues as these services and networks are going to interact with each other and with other networks including the Internet. In this project, our overarching goal is examine the main threats in connected vehicles applications under different adversarial models and deployments.



    Are Self-Driving Cars Secure? Evasion Attacks against Deep Neural Networks for Steering Angle Prediction. Alesia Chernikova, Alina Oprea, Cristina Nita-Rotaru and Baekgyu Kim. IEEE Workshop on the Internet of Safe Things, Co-located with IEEE Security and Privacy 2019. [arXiv]
    Network and System Level Security in Connected Vehicle Applications. Hengyi Liang, Matthew Jagielski, Bowen Zheng, Chung-Wei Lin, Eunsuk Kang, Shinichi Shiraishi, Cristina Nita-Rotaru, Qi Zhu. ICCAD 2018.
    Threat Detection for Collaborative Adaptive Cruise Control in Connected Cars. Matthew Jagielski, Nicholas Jones, Chung-Wei Lin, Cristina Nita-Rotaru, and Shinichi Shiraishi. In Proceedings of ACM Conference on Security and Privacy in Wireless Networks, 2018. Short paper. [PDF]


    Current Members

    • Matthew Jagielski
    • Alesia Chernikova


This project is a collaboration with Toyota ITC.