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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DRAWN APART: A Device Identification Technique based on Remote...

Tomer Laor (Ben-Gurion Univ. of the Negev), Naif Mehanna (Univ. Lille, CNRS, Inria), Antonin Durey (Univ. Lille, CNRS, Inria), Vitaly Dyadyuk (Ben-Gurion Univ. of the Negev), Pierre Laperdrix (Univ. Lille, CNRS, Inria), Clémentine Maurice (Univ. Lille, CNRS, Inria), Yossi Oren (Ben-Gurion Univ. of the Negev), Romain Rouvoy (Univ. Lille, CNRS, Inria / IUF), Walter Rudametkin…

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ditto: WAN Traffic Obfuscation at Line Rate

Roland Meier (ETH Zürich), Vincent Lenders (armasuisse), Laurent Vanbever (ETH Zürich)

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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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DrawnApart: A Deep-Learning Enhanced GPU Fingerprinting Technique

Naif Mehanna (University of Lille, CNRS, Inria), Tomer Laor (Ben-Gurion University of the Negev)

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