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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Him of Many Faces: Characterizing Billion-scale Adversarial and Benign...

Shujiang Wu (Johns Hopkins University), Pengfei Sun (F5, Inc.), Yao Zhao (F5, Inc.), Yinzhi Cao (Johns Hopkins University)

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Drone Security and the Mysterious Case of DJI's DroneID

Nico Schiller (Ruhr-Universität Bochum), Merlin Chlosta (CISPA Helmholtz Center for Information Security), Moritz Schloegel (Ruhr-Universität Bochum), Nils Bars (Ruhr University Bochum), Thorsten Eisenhofer (Ruhr University Bochum), Tobias Scharnowski (Ruhr-University Bochum), Felix Domke (Independent), Lea Schönherr (CISPA Helmholtz Center for Information Security), Thorsten Holz (CISPA Helmholtz Center for Information Security)

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InfoMasker: Preventing Eavesdropping Using Phoneme-Based Noise

Peng Huang (Zhejiang University), Yao Wei (Zhejiang University), Peng Cheng (Zhejiang University), Zhongjie Ba (Zhejiang University), Li Lu (Zhejiang University), Feng Lin (Zhejiang University), Fan Zhang (Zhejiang University), Kui Ren (Zhejiang University)

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