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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Towards Automatic and Precise Heap Layout Manipulation for General-Purpose...

Runhao Li (National University of Defense Technology), Bin Zhang (National University of Defense Technology), Jiongyi Chen (National University of Defense Technology), Wenfeng Lin (National University of Defense Technology), Chao Feng (National University of Defense Technology), Chaojing Tang (National University of Defense Technology)

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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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Short: Certifiably Robust Perception Against Adversarial Patch Attacks: A...

Chong Xiang (Princeton University), Chawin Sitawarin (University of California, Berkeley), Tong Wu (Princeton University), Prateek Mittal (Princeton University)

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Parakeet: Practical Key Transparency for End-to-End Encrypted Messaging

Harjasleen Malvai (UIUC/IC3), Lefteris Kokoris-Kogias (IST Austria), Alberto Sonnino (Mysten Labs), Esha Ghosh (Microsoft Research), Ercan Oztürk (Meta), Kevin Lewi (Meta), Sean Lawlor (Meta)

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