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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NSFuzz: Towards Efficient and State-Aware Network Service Fuzzing

Shisong Qin (Tsinghua University), Fan Hu (State Key Laboratory of Mathematical Engineering and Advanced Computing), Bodong Zhao (Tsinghua University), Tingting Yin (Tsinghua University), Chao Zhang (Tsinghua University)

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RamBoAttack: A Robust and Query Efficient Deep Neural Network...

Viet Quoc Vo (The University of Adelaide), Ehsan Abbasnejad (The University of Adelaide), Damith C. Ranasinghe (University of Adelaide)

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Trust and Privacy Expectations during Perilous Times of Contact...

Habiba Farzand (University of Glasgow), Florian Mathis (University of Glasgow), Karola Marky (University of Glasgow), Mohamed Khamis (University of Glasgow)

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