Demo: Security of Camera-based Perception for Autonomous Driving under Adversarial Attack

Abstract

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 endto-end consequences on a representative autonomous driving system in a simulator.