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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Understanding the Internet-Wide Vulnerability Landscape for ROS-based Robotic Vehicles...

Wentao Chen, Sam Der, Yunpeng Luo, Fayzah Alshammari, Qi Alfred Chen (University of California, Irvine)

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Real Threshold ECDSA

Harry W. H. Wong (The Chinese University of Hong Kong), Jack P. K. Ma (The Chinese University of Hong Kong), Hoover H. F. Yin (The Chinese University of Hong Kong), Sherman S. M. Chow (The Chinese University of Hong Kong)

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Thwarting Smartphone SMS Attacks at the Radio Interface Layer

Haohuang Wen (Ohio State University), Phillip Porras (SRI International), Vinod Yegneswaran (SRI International), Zhiqiang Lin (Ohio State University)

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HeteroScore: Evaluating and Mitigating Cloud Security Threats Brought by...

Chongzhou Fang (University of California, Davis), Najmeh Nazari (University of California, Davis), Behnam Omidi (George Mason University), Han Wang (Temple University), Aditya Puri (Foothill High School, Pleasanton, CA), Manish Arora (LearnDesk, Inc.), Setareh Rafatirad (University of California, Davis), Houman Homayoun (University of California, Davis), Khaled N. Khasawneh (George Mason University)

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