Li Yue, Zheming Li, Tingting Yin, and Chao Zhang (Tsinghua University)

Modern vehicles have many electronic control units (ECUs) connected to the Controller Area Network (CAN) bus, which have few security features in design and are vulnerable to cyber attacks. Researchers have proposed solutions like intrusion detection systems (IDS) to mitigate such threats. We presented a novel attack, CANCloak, which can deceive two ECUs with one CAN data frame, and therefore can bypass IDS detection or cause vehicle malfunction. In this attack, assuming a malicious transmitter is controlled by the adversary, one crafted CAN data frame can be transmitted to a target receiver, while other ECUs shall not receive that frame nor raise any error. We have setup a physical test environment and evaluated the effectiveness of this attack. Evaluation results showed that success rate of CANCloak reaches up to 99.7%, while the performance depends on the attack payload and sample point settings of victim receivers, independent from bus bit rate.

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PASS: A System-Driven Evaluation Platform for Autonomous Driving Safety...

Zhisheng Hu (Baidu Security), Junjie Shen (UC Irvine), Shengjian Guo (Baidu Security), Xinyang Zhang (Baidu Security), Zhenyu Zhong (Baidu Security), Qi Alfred Chen (UC Irvine) and Kang Li (Baidu Security)

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Demo #7: A Simulator for Cooperative and Automated Driving...

Mohammed Lamine Bouchouia (Telecom Paris - Institut Polytechnique de Paris), Jean-Philippe Monteuuis (Qualcomm Technologies Inc), Houda Labiod (Telecom Paris - Institut Polytechnique de Paris), Ons Jelassi (Telecom Paris - Institut Polytechnique de Paris), Wafa Ben Jaballah (Thales) and Jonathan Petit (Qualcomm Technologies Inc)

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Andreas Unterweger, Fabian Knirsch, Clemens Brunner and Dominik Engel (Center for Secure Energy Informatics, Salzburg University of Applied Sciences, Puch bei Hallein, Austria)

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Junjie Shen, Jun Yeon Won, Zeyuan Chen and Qi Alfred Chen (UC Irvine)

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