Aiping Xiong (Pennsylvania State University), Zekun Cai (Pennsylvania State University) and Tianhao Wang (University of Virginia)

Individuals’ interactions with connected autonomous vehicles (CAVs) involve sharing various data in a ubiquitous manner, raising novel challenges for privacy. The human factors of privacy must first be understood to promote consumers’ acceptance of CAVs. To inform the privacy research in the context of CAVs, we discuss how the emerging technologies development of CAV poses new privacy challenges for drivers and passengers. We argue that the privacy design of CAVs should adopt a user-centered approach, which integrates human factors into the development and deployment of privacy-enhancing technologies, such as differential privacy.

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WIP: Infrastructure-Aided Defense for Autonomous Driving Systems: Opportunities and...

Yunpeng Luo (UC Irvine), Ningfei Wang (UC Irvine), Bo Yu (PerceptIn), Shaoshan Liu (PerceptIn) and Qi Alfred Chen (UC Irvine)

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SynthCT: Towards Portable Constant-Time Code

Sushant Dinesh (University of Illinois at Urbana Champaign), Grant Garrett-Grossman (University of Illinois at Urbana Champaign), Christopher W. Fletcher (University of Illinois at Urbana Champaign)

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CANCloak: Deceiving Two ECUs with One Frame

Li Yue, Zheming Li, Tingting Yin, and Chao Zhang (Tsinghua University)

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Demo: A Simulator for Cooperative and Automated Driving Security

Mohammed Lamine Bouchouia (Telecom Paris - Institut Polytechnique de Paris), Jean-Philippe Monteuuis (Qualcomm), Houda Labiod (Telecom Paris - Institut Polytechnique de Paris), Ons Jelassi, Wafa Ben Jaballah (Thales) and Jonathan Petit (Telecom Paris - Institut Polytechnique de Paris)

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