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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Securing CAN Traffic on J1939 Networks

Jeremy Daily, David Nnaji, and Ben Ettlinger (Colorado State University)

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Impact Evaluation of Falsified Data Attacks on Connected Vehicle...

Shihong Huang (University of Michigan, Ann Arbor), Yiheng Feng (Purdue University), Wai Wong (University of Michigan, Ann Arbor), Qi Alfred Chen (UC Irvine), Z. Morley Mao and Henry X. Liu (University of Michigan, Ann Arbor) Best Paper Award Runner-up ($200 cash prize)!

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Detecting Obfuscated Function Clones in Binaries using Machine Learning

Michael Pucher (University of Vienna), Christian Kudera (SBA Research), Georg Merzdovnik (SBA Research)

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