Alireza Mohammadi (University of Michigan-Dearborn), Hafiz Malik (University of Michigan-Dearborn) and Masoud Abbaszadeh (GE Global Research)

Recent automotive hacking incidences have demonstrated that when an adversary manages to gain access to a safety-critical CAN, severe safety implications will ensue. Under such threats, this paper explores the capabilities of an adversary who is interested in engaging the car brakes at full speed and would like to cause wheel lockup conditions leading to catastrophic road injuries. This paper shows that the physical capabilities of a CAN attacker can be studied through the lens of closed-loop attack policy design. In particular, it is demonstrated that the adversary can cause wheel lockups by means of closed-loop attack policies for commanding the frictional brake actuators under a limited knowledge of the tire-road interaction characteristics. The effectiveness of the proposed wheel lockup attack policy is shown via numerical simulations under different road conditions.

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Fooling the Eyes of Autonomous Vehicles: Robust Physical Adversarial...

Wei Jia (School of Cyber Science and Engineering, Huazhong University of Science and Technology), Zhaojun Lu (School of Cyber Science and Engineering, Huazhong University of Science and Technology), Haichun Zhang (Huazhong University of Science and Technology), Zhenglin Liu (Huazhong University of Science and Technology), Jie Wang (Shenzhen Kaiyuan Internet Security Co., Ltd), Gang Qu (University…

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VPNInspector: Systematic Investigation of the VPN Ecosystem

Reethika Ramesh (University of Michigan), Leonid Evdokimov (Independent), Diwen Xue (University of Michigan), Roya Ensafi (University of Michigan)

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Demo #14: In-Vehicle Communication Using Named Data Networking

Zachariah Threet (Tennessee Tech), Christos Papadopoulos (University of Memphis), Proyash Poddar (Florida International University), Alex Afanasyev (Florida International University), William Lambert (Tennessee Tech), Haley Burnell (Tennessee Tech), Sheikh Ghafoor (Tennessee Tech) and Susmit Shannigrahi (Tennessee Tech)

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Dissecting American Fuzzy Lop – A FuzzBench Evaluation

Andrea Fioraldi (EURECOM), Alessandro Mantovani (EURECOM), Dominik Maier (TU Berlin), Davide Balzarotti (EURECOM)

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