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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ChargePrint: A Framework for Internet-Scale Discovery and Security Analysis...

Tony Nasr (Concordia University), Sadegh Torabi (George Mason University), Elias Bou-Harb (University of Texas at San Antonio), Claude Fachkha (University of Dubai), Chadi Assi (Concordia University)

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The evolution of program analysis approaches in the era...

Alex Matrosov (CEO and Founder of Binarly Inc.)

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Preventing SIM Box Fraud Using Device Model Fingerprinting

BeomSeok Oh (KAIST), Junho Ahn (KAIST), Sangwook Bae (KAIST), Mincheol Son (KAIST), Yonghwa Lee (KAIST), Min Suk Kang (KAIST), Yongdae Kim (KAIST)

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REDsec: Running Encrypted Discretized Neural Networks in Seconds

Lars Wolfgang Folkerts (University of Delaware), Charles Gouert (University of Delaware), Nektarios Georgios Tsoutsos (University of Delaware)

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