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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CROW: Code Diversification for WebAssembly

Javier Cabrera Arteaga, Orestis Floros, Benoit Baudry, Martin Monperrus (KTH Royal Institute of Technology), Oscar Vera Perez (Univ Rennes, Inria,...

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Cross-National Study on Phishing Resilience

Shakthidhar Reddy Gopavaram (Indiana University), Jayati Dev (Indiana University), Marthie Grobler (CSIRO’s Data61), DongInn Kim (Indiana University), Sanchari Das (University...

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Taking a Closer Look at the Alexa Skill Ecosystem

Christopher Lentzsch (Ruhr-Universität Bochum), Anupam Das (North Carolina State University)

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Towards a TEE-based V2V Protocol for Connected and Autonomous...

Mohit Kumar Jangid (Ohio State University) and Zhiqiang Lin (Ohio State University)

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