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: Interrupt Attack on TEE-protected Robotic Vehicles

Mulong Luo (Cornell University) and G. Edward Suh (Cornell University)

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D-Box: DMA-enabled Compartmentalization for Embedded Applications

Alejandro Mera (Northeastern University), Yi Hui Chen (Northeastern University), Ruimin Sun (Northeastern University), Engin Kirda (Northeastern University), Long Lu (Northeastern University)

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GPSKey: GPS based Secret Key Establishment for Intra-Vehicle Environment

Edwin Yang (University of Oklahoma) and Song Fang (University of Oklahoma)

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