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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Tetrad: Actively Secure 4PC for Secure Training and Inference

Nishat Koti (IISc Bangalore), Arpita Patra (IISc Bangalore), Rahul Rachuri (Aarhus University, Denmark), Ajith Suresh (IISc, Bangalore)

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A Framework for Consistent and Repeatable Controller Area Network...

Paul Agbaje (University of Texas at Arlington), Afia Anjum (University of Texas at Arlington), Arkajyoti Mitra (University of Texas at Arlington), Gedare Bloom (University of Colorado Colorado Springs) and Habeeb Olufowobi (University of Texas at Arlington)

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DeepSight: Mitigating Backdoor Attacks in Federated Learning Through Deep...

Phillip Rieger (Technical University of Darmstadt), Thien Duc Nguyen (Technical University of Darmstadt), Markus Miettinen (Technical University of Darmstadt), Ahmad-Reza Sadeghi (Technical University of Darmstadt)

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Time-Based CAN Intrusion Detection Benchmark

Deborah Blevins (University of Kentucky), Pablo Moriano, Robert Bridges, Miki Verma, Michael Iannacone, and Samuel Hollifield (Oak Ridge National Laboratory)

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