Zachary Depp, Halit Bugra Tulay, C. Emre Koksal (The Ohio State University)

The traditional vehicular roll-jam attack is an effective means to gain access to the target vehicle by jamming and recording key fob inputs from a victim. However, it requires specific knowledge of the attack surface, and delicate tuning of software-defined radio parameters. We have developed an enhanced version of the roll-jam attack that uses a known noise signal for jamming, in contrast to the additive white Gaussian noise that is typically used in the attack. Using a known noise signal allows for less strict tuning of the software-defined radios used in the attack, and allows for digital noise removal of the recorded input to enhance the replay attack.

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AVMON: Securing Autonomous Vehicles by Learning Control Invariants and...

Ahmed Abdo, Sakib Md Bin Malek, Xuanpeng Zhao, Nael Abu-Ghazaleh (University of California, Riverside)

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Bridging the Privacy Gap: Enhanced User Consent Mechanisms on...

Carl Magnus Bruhner (Linkoping University), David Hasselquist (Linkoping University, Sectra Communications), Niklas Carlsson (Linkoping University)

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WIP: Adversarial Retroreflective Patches: A Novel Stealthy Attack on...

Go Tsuruoka (Waseda University), Takami Sato, Qi Alfred Chen (University of California, Irvine), Kazuki Nomoto, Ryunosuke Kobayashi, Yuna Tanaka (Waseda University), Tatsuya Mori (Waseda University/NICT/RIKEN)

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