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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Securing Automotive Software Supply Chains (Long)

Marina Moore, Aditya Sirish A Yelgundhalli (New York University), Justin Cappos (NYU)

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Augmented Reality’s Potential for Identifying and Mitigating Home Privacy...

Stefany Cruz (Northwestern University), Logan Danek (Northwestern University), Shinan Liu (University of Chicago), Christopher Kraemer (Georgia Institute of Technology), Zixin Wang (Zhejiang University), Nick Feamster (University of Chicago), Danny Yuxing Huang (New York University), Yaxing Yao (University of Maryland), Josiah Hester (Georgia Institute of Technology)

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MetaWave: Attacking mmWave Sensing with Meta-material-enhanced Tags

Xingyu Chen (University of Colorado Denver), Zhengxiong Li (University of Colorado Denver), Baicheng Chen (University of California San Diego), Yi Zhu (SUNY at Buffalo), Chris Xiaoxuan Lu (University of Edinburgh), Zhengyu Peng (Aptiv), Feng Lin (Zhejiang University), Wenyao Xu (SUNY Buffalo), Kui Ren (Zhejiang University), Chunming Qiao (SUNY at Buffalo)

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