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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Breaking and Fixing Virtual Channels: Domino Attack and Donner

Lukas Aumayr (TU Wien), Pedro Moreno-Sanchez (IMDEA Software Institute), Aniket Kate (Purdue University / Supra), Matteo Maffei (Christian Doppler Laboratory Blockchain Technologies for the Internet of Things / TU Wien)

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Location Spoofing Attacks on Autonomous Fleets

Jinghan Yang, Andew Estornell, Yevgeniy Vorobeychik (Washington University in St. Louis)

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Short: Rethinking Secure Pairing in Drone Swarms

Muslum Ozgur Ozmen, Habiba Farrukh, Hyungsub Kim, Antonio Bianchi, Z. Berkay Celik (Purdue University)

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