Christopher DiPalma, Ningfei Wang, Takami Sato, and Qi Alfred Chen (UC Irvine)

Robust perception is crucial for autonomous vehicle security. In this work, we design a practical adversarial patch attack against camera-based obstacle detection. We identify that the back of a box truck is an effective attack vector. We also improve attack robustness by considering a variety of input frames associated with the attack scenario. This demo includes videos that show our attack can cause end-to-end consequences on a representative autonomous driving system in a simulator.

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Debunking Exposure Notification

Serge Vaudenay, EPFL, Switzerland

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Detecting DolphinAttacks Based on Microphone Array

Guoming Zhang, Xiaoyu Ji (Zhejiang University)

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Demo #9: Attacking Multi-Sensor Fusion based Localization in High-Level...

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

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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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