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

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

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The Taming of the Stack: Isolating Stack Data from...

Kaiming Huang (Penn State University), Yongzhe Huang (Penn State University), Mathias Payer (EPFL), Zhiyun Qian (UC Riverside), Jack Sampson (Penn State University), Gang Tan (Penn State University), Trent Jaeger (Penn State University)

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Detecting CAN Masquerade Attacks with Signal Clustering Similarity

Pablo Moriano (Oak Ridge National Laboratory), Robert A. Bridges (Oak Ridge National Laboratory) and Michael D. Iannacone (Oak Ridge National Laboratory)

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