Demo #15: Remote Adversarial Attack on Automated Lane Centering

Yulong Cao (University of Michigan), Yanan Guo (University of Pittsburgh), Takami Sato (UC Irvine), Qi Alfred Chen (UC Irvine), Z. Morley Mao (University of Michigan) and Yueqiang Cheng (NIO)

Advanced driver-assistance systems (ADAS) are widely used by modern vehicle manufacturers to automate, adapt and enhance vehicle technology for safety and better driving. In this work, we design a practical attack against automated lane centering (ALC), a crucial functionality of ADAS, with remote adversarial patches. We identify that the back of a vehicle is an effective attack vector and improve the attack robustness by considering various input frames. The demo includes videos that show our attack can divert victim vehicle out of lane on a representative ADAS, Openpilot, in a simulator.

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Multi-Certificate Attacks against Proof-of-Elapsed-Time and Their Countermeasures

Huibo Wang (Baidu Security), Guoxing Chen (Shanghai Jiao Tong University), Yinqian Zhang (Southern University of Science and Technology), Zhiqiang Lin (Ohio State University)

Demo #4: Recovering Autonomous Robotic Vehicles from Physical Attacks

Pritam Dash (University of British Columbia) and Karthik Pattabiraman (University of British Columbia)

Progressive Scrutiny: Incremental Detection of UBI bugs in the...

Yizhuo Zhai (University of California, Riverside), Yu Hao (University of California, Riverside), Zheng Zhang (University of California, Riverside), Weiteng Chen (University of California, Riverside), Guoren Li (University of California, Riverside), Zhiyun Qian (University of California, Riverside), Chengyu Song (University of California, Riverside), Manu Sridharan (University of California, Riverside), Srikanth V. Krishnamurthy (University of California, Riverside),…