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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podft: On Accelerating Dynamic Taint Analysis with Precise Path...

Zhiyou Tian (Xidian University), Cong Sun (Xidian University), Dongrui Zeng (Palo Alto Networks), Gang Tan (Pennsylvania State University)

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dewolf: Improving Decompilation by leveraging User Surveys

Steffen Enders, Eva-Maria C. Behner, Niklas Bergmann, Mariia Rybalka, Elmar Padilla (Fraunhofer FKIE, Germany), Er Xue Hui, Henry Low, Nicholas Sim (DSO National Laboratories, Singapore)

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Exploiting Transport Protocol Vulnerabilities in SAE J1939 Networks

Rik Chatterjee, Subhojeet Mukherjee, Jeremy Daily (Colorado State University)

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Post-GDPR Threat Hunting on Android Phones: Dissecting OS-level Safeguards...

Mark Huasong Meng (National University of Singapore), Qing Zhang (ByteDance), Guangshuai Xia (ByteDance), Yuwei Zheng (ByteDance), Yanjun Zhang (The University of Queensland), Guangdong Bai (The University of Queensland), Zhi Liu (ByteDance), Sin G. Teo (Agency for Science, Technology and Research), Jin Song Dong (National University of Singapore)

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