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: Adversarial Object-Evasion Attack Detection in Autonomous Driving Contexts:...

Rao Li (The Pennsylvania State University), Shih-Chieh Dai (Pennsylvania State University), Aiping Xiong (Penn State University)

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WIP: Modeling and Detecting Falsified Vehicle Trajectories Under Data...

Jun Ying, Yiheng Feng (Purdue University), Qi Alfred Chen (University of California, Irvine), Z. Morley Mao (University of Michigan and Google)

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DOITRUST: Dissecting On-chain Compromised Internet Domains via Graph Learning

Shuo Wang (CSIRO's Data61 & Cybersecurity CRC, Australia), Mahathir Almashor (CSIRO's Data61 & Cybersecurity CRC, Australia), Alsharif Abuadbba (CSIRO's Data61 & Cybersecurity CRC, Australia), Ruoxi Sun (CSIRO's Data61), Minhui Xue (CSIRO's Data61), Calvin Wang (CSIRO's Data61), Raj Gaire (CSIRO's Data61 & Cybersecurity CRC, Australia), Surya Nepal (CSIRO's Data61 & Cybersecurity CRC, Australia), Seyit Camtepe (CSIRO's…

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