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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Folk Models of Misinformation on Social Media

Filipo Sharevski (DePaul University), Amy Devine (DePaul University), Emma Pieroni (DePaul University), Peter Jachim (DePaul University)

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PPA: Preference Profiling Attack Against Federated Learning

Chunyi Zhou (Nanjing University of Science and Technology), Yansong Gao (Nanjing University of Science and Technology), Anmin Fu (Nanjing University of Science and Technology), Kai Chen (Chinese Academy of Science), Zhiyang Dai (Nanjing University of Science and Technology), Zhi Zhang (CSIRO's Data61), Minhui Xue (CSIRO's Data61), Yuqing Zhang (University of Chinese Academy of Science)

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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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