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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WIP: Body Posture Analysis as an Objective Measurement for...

Cherin Lim, Tianhao Xu, Prashanth Rajivan (University of Washington)

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Investigating User Behaviour Towards Fake News on Social Media...

Yasmeen Abdrabou (University of the Bundeswehr Munich), Elisaveta Karypidou (LMU Munich), Florian Alt (University of the Bundeswehr Munich), Mariam Hassib (University of the Bundeswehr Munich)

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Reverse Engineering of Multiplexed CAN Frames (Long)

Alessio Buscemi, Thomas Engel (SnT, University of Luxembourg), Kang G. Shin (The University of Michigan)

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OCPPStorm: A Comprehensive Fuzzing Tool for OCPP Implementations (Long)

Gaetano Coppoletta (University of Illinois Chicago), Rigel Gjomemo (Discovery Partners Institute, University of Illinois), Amanjot Kaur, Nima Valizadeh (Cardiff University), Venkat Venkatakrishnan (Discovery Partners Institute, University of Illinois), Omer Rana (Cardiff University)

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