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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Detecting Unknown Encrypted Malicious Traffic in Real Time via...

Chuanpu Fu (Tsinghua University), Qi Li (Tsinghua University), Ke Xu (Tsinghua University)

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WIP: An Adaptive High Frequency Removal Attack to Bypass...

Yuki Hayakawa (Keio University), Takami Sato (University of California, Irvine), Ryo Suzuki, Kazuma Ikeda, Ozora Sako, Rokuto Nagata (Keio University), Qi Alfred Chen (University of California, Irvine), Kentaro Yoshioka (Keio University)

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Privacy-Preserving Database Fingerprinting

Tianxi Ji (Texas Tech University), Erman Ayday (Case Western Reserve University), Emre Yilmaz (University of Houston-Downtown), Ming Li (CSE Department The University of Texas at Arlington), Pan Li (Case Western Reserve University)

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