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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Forensic Analysis of Configuration-based Attacks

Muhammad Adil Inam (University of Illinois at Urbana-Champaign), Wajih Ul Hassan (University of Illinois at Urbana-Champaign), Ali Ahad (University of Virginia), Adam Bates (University of Illinois at Urbana-Champaign), Rashid Tahir (University of Prince Mugrin), Tianyin Xu (University of Illinois at Urbana-Champaign), Fareed Zaffar (LUMS)

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Securing CAN Traffic on J1939 Networks

Jeremy Daily, David Nnaji, and Ben Ettlinger (Colorado State 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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FedCRI: Federated Mobile Cyber-Risk Intelligence

Hossein Fereidooni (Technical University of Darmstadt), Alexandra Dmitrienko (University of Wuerzburg), Phillip Rieger (Technical University of Darmstadt), Markus Miettinen (Technical University of Darmstadt), Ahmad-Reza Sadeghi (Technical University of Darmstadt), Felix Madlener (KOBIL)

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