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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Automata-Based Automated Detection of State Machine Bugs in Protocol...

Paul Fiterau-Brostean (Uppsala University, Sweden), Bengt Jonsson (Uppsala University, Sweden), Konstantinos Sagonas (Uppsala University, Sweden and National Technical University of Athens, Greece), Fredrik Tåquist (Uppsala University, Sweden)

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Machine Unlearning of Features and Labels

Alexander Warnecke (TU Braunschweig), Lukas Pirch (TU Braunschweig), Christian Wressnegger (Karlsruhe Institute of Technology (KIT)), Konrad Rieck (TU Braunschweig)

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WIP: Savvy: Trustworthy Autonomous Vehicles Architecture

Ali Shoker, Rehana Yasmin, Paulo Esteves-Verissimo (Resilient Computing & Cybersecurity Center (RC3), KAUST)

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