Zhisheng Hu (Baidu), Shengjian Guo (Baidu) and Kang Li (Baidu)

In this demo, we disclose a potential bug in the Tesla Full Self-Driving (FSD) software. A vulnerable FSD vehicle can be deterministically tricked to run a red light. Attackers can cause a victim vehicle to behave in such ways without tampering or interfering with any sensors or physically accessing the vehicle. We infer that such behavior is caused by Tesla FSD’s decision system failing to take latest perception signals once it enters a specific mode. We call such problematic behavior Pringles Syndrome. Our study on multiple other autonomous driving implementations shows that this failed state update is a common failure pattern that specially needs attentions in autonomous driving software tests and developments.

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Demo #1: Security of Multi-Sensor Fusion based Perception in...

Yulong Cao (University of Michigan), Ningfei Wang (UC, Irvine), Chaowei Xiao (Arizona State University), Dawei Yang (University of Michigan), Jin Fang (Baidu Research), Ruigang Yang (University of Michigan), Qi Alfred Chen (UC, Irvine), Mingyan Liu (University of Michigan) and Bo Li (University of Illinois at Urbana-Champaign)

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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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ATTEQ-NN: Attention-based QoE-aware Evasive Backdoor Attacks

Xueluan Gong (Wuhan University), Yanjiao Chen (Zhejiang University), Jianshuo Dong (Wuhan University), Qian Wang (Wuhan University)

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Phishing awareness and education – When to best remind?

Benjamin Maximilian Berens (SECUSO, Karlsruhe Institute of Technology), Katerina Dimitrova, Mattia Mossano (SECUSO, Karlsruhe Institute of Technology), Melanie Volkamer (SECUSO, Karlsruhe Institute of Technology)

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