Alireza Mohammadi (University of Michigan-Dearborn) and Hafiz Malik (University of Michigan-Dearborn)

Motivated by ample evidence in the automotive cybersecurity literature that the car brake ECUs can be maliciously reprogrammed, it has been shown that an adversary who can directly control the frictional brake actuators can induce wheel lockup conditions despite having a limited knowledge of the tire-road interaction characteristics. In this paper, we investigate the destabilizing effect of such wheel lockup attacks on the lateral motion stability of vehicles from a robust stability perspective. Furthermore, we propose a quadratic programming (QP) problem that the adversary can solve for finding the optimal destabilizing longitudinal slip reference values.

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Model-Agnostic Defense for Lane Detection against Adversarial Attack

Henry Xu, An Ju, and David Wagner (UC Berkeley) Baidu Security Auto-Driving Security Award Winner ($1000 cash prize)!

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Multi-Certificate Attacks against Proof-of-Elapsed-Time and Their Countermeasures

Huibo Wang (Baidu Security), Guoxing Chen (Shanghai Jiao Tong University), Yinqian Zhang (Southern University of Science and Technology), Zhiqiang Lin (Ohio State University)

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insecure:// Vulnerability Analysis of URI Scheme Handling in Android...

Abdulla Aldoseri (University of Birmingham) and David Oswald (University of Birmingham)

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Demo #9: Dynamic Time Warping as a Tool for...

Mars Rayno (Colorado State University) and Jeremy Daily (Colorado State University)

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