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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Context-Sensitive and Directional Concurrency Fuzzing for Data-Race Detection

Zu-Ming Jiang (Tsinghua University), Jia-Ju Bai (Tsinghua University), Kangjie Lu (University of Minnesota), Shi-Min Hu (Tsinghua University)

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

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DeepSight: Mitigating Backdoor Attacks in Federated Learning Through Deep...

Phillip Rieger (Technical University of Darmstadt), Thien Duc Nguyen (Technical University of Darmstadt), Markus Miettinen (Technical University of Darmstadt), Ahmad-Reza Sadeghi (Technical University of Darmstadt)

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LogicMEM: Automatic Profile Generation for Binary-Only Memory Forensics via...

Zhenxiao Qi (UC Riverside), Yu Qu (UC Riverside), Heng Yin (UC Riverside)

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