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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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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Demo #7: Automated Tracking System For LiDAR Spoofing Attacks...

Yulong Cao, Jiaxiang Ma, Kevin Fu (University of Michigan), Sara Rampazzi (University of Florida), and Z. Morley Mao (University of Michigan) Best Demo Award Runner-up ($200 cash prize)!

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Preventing Kernel Hacks with HAKCs

Derrick McKee (Purdue University), Yianni Giannaris (MIT CSAIL), Carolina Ortega (MIT CSAIL), Howard Shrobe (MIT CSAIL), Mathias Payer (EPFL), Hamed Okhravi (MIT Lincoln Laboratory), Nathan Burow (MIT Lincoln Laboratory)

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