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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Model-Agnostic Defense for Lane Detection against Adversarial Attack

Henry Xu, An Ju, and David Wagner (UC Berkeley) Baidu Security Auto-Driving Security Award Winner ($1000 cash prize)!

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Demo #5: Securing Heavy Vehicle Diagnostics

Jeremy Daily, David Nnaji, and Ben Ettlinger (Colorado State University)

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Chunked-Cache: On-Demand and Scalable Cache Isolation for Security Architectures

Ghada Dessouky (Technical University of Darmstadt), Emmanuel Stapf (Technical University of Darmstadt), Pouya Mahmoody (Technical University of Darmstadt), Alexander Gruler (Technical University of Darmstadt), Ahmad-Reza Sadeghi (Technical University of Darmstadt)

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