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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LogicMEM: Automatic Profile Generation for Binary-Only Memory Forensics via...

Zhenxiao Qi (UC Riverside), Yu Qu (UC Riverside), Heng Yin (UC Riverside)

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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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Building the VPNalyzer System

Reethika Ramesh (University of Michigan), Leonid Evdokimov (Independent), Diwen Xue, Roya Ensafi (University of Michigan)

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Fuzzing Configurations of Program Options

Zenong Zhang (University of Texas at Dallas), George Klees (University of Maryland), Eric Wang (Poolesville High School), Michael Hicks (University of Maryland), Shiyi Wei (University of Texas at Dallas)

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