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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RAI2: Responsible Identity Audit Governing the Artificial Intelligence

Tian Dong (Shanghai Jiao Tong University), Shaofeng Li (Shanghai Jiao Tong University), Guoxing Chen (Shanghai Jiao Tong University), Minhui Xue (CSIRO's Data61), Haojin Zhu (Shanghai Jiao Tong University), Zhen Liu (Shanghai Jiao Tong University)

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Firefly: Spoofing Earth Observation Satellite Data through Radio Overshadowing

Edd Salkield, Sebastian Köhler, Simon Birnbach, Richard Baker (University of Oxford). Martin Strohmeier (armasuisse S+T), Ivan Martinovic (University of Oxford) Presenter: Edd Salkield

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MyTEE: Own the Trusted Execution Environment on Embedded Devices

Seungkyun Han (Chungnam National University), Jinsoo Jang (Chungnam National University)

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Analyzing the Patterns and Behavior of Users When Detecting...

Nick Ceccio, Naman Gupta, Majed Almansoori, Rahul Chatterjee (University of Wisconsin-Madison)

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