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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Zhisheng Hu (Baidu Security), Junjie Shen (UC Irvine), Shengjian Guo (Baidu Security), Xinyang Zhang (Baidu Security), Zhenyu Zhong (Baidu Security),...

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Model-Agnostic Defense for Lane Detection against Adversarial Attack

Henry Xu, An Ju, and David Wagner (UC Berkeley) Baidu Security Auto-Driving Security Award Winner ($1000 cash prize)!

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GPSKey: GPS based Secret Key Establishment for Intra-Vehicle Environment

Edwin Yang (University of Oklahoma) and Song Fang (University of Oklahoma)

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WIP: Interrupt Attack on TEE-protected Robotic Vehicles

Mulong Luo (Cornell University) and G. Edward Suh (Cornell University)

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