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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Operationalizing Cybersecurity Research Ethics Review: From Principles and Guidelines...

Dennis Reidsma, Jeroen van der Ham, and Andrea Continella (University of Twente)

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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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AutoWatch: Learning Driver Behavior with Graphs for Auto Theft...

Paul Agbaje, Abraham Mookhoek, Afia Anjum, Arkajyoti Mitra (University of Texas at Arlington), Mert D. Pesé (Clemson University), Habeeb Olufowobi (University of Texas at Arlington)

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CHKPLUG: Checking GDPR Compliance of WordPress Plugins via Cross-language...

Faysal Hossain Shezan (University of Virginia), Zihao Su (University of Virginia), Mingqing Kang (Johns Hopkins University), Nicholas Phair (University of Virginia), Patrick William Thomas (University of Virginia), Michelangelo van Dam (in2it), Yinzhi Cao (Johns Hopkins University), Yuan Tian (UCLA)

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