Diego Ortiz, Leilani Gilpin, Alvaro A. Cardenas (University of California, Santa Cruz)

Autonomous vehicles must operate in a complex environment with various social norms and expectations. While most of the work on securing autonomous vehicles has focused on safety, we argue that we also need to monitor for deviations from various societal “common sense” rules to identify attacks against autonomous systems. In this paper, we provide a first approach to encoding and understanding these common-sense driving behaviors by semi-automatically extracting rules from driving manuals. We encode our driving rules in a formal specification and make our rules available online for other researchers.

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WIP: Towards Practical LiDAR Spoofing Attack against Vehicles Driving...

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

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SynthDB: Synthesizing Database via Program Analysis for Security Testing...

An Chen (University of Georgia), Jiho Lee (University of Virginia), Basanta Chaulagain (University of Georgia), Yonghwi Kwon (University of Virginia), Kyu Hyung Lee (University of Georgia)

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Accurate Compiler and Optimization Independent Function Identification Using Program...

Derrick McKee (Purdue University), Nathan Burow (MIT Lincoln Laboratory), Mathias Payer (EPFL)

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ChargePrint: A Framework for Internet-Scale Discovery and Security Analysis...

Tony Nasr (Concordia University), Sadegh Torabi (George Mason University), Elias Bou-Harb (University of Texas at San Antonio), Claude Fachkha (University of Dubai), Chadi Assi (Concordia University)

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