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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Analyzing and Creating Malicious URLs: A Comparative Study on...

Vincent Drury (IT-Security Research Group, RWTH Aachen University), Rene Roepke (Learning Technologies Research Group, RWTH Aachen University), Ulrik Schroeder (Learning Technologies Research Group, RWTH Aachen University), Ulrike Meyer (IT-Security Research Group, RWTH Aachen University)

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Demo #6: Impact of Stealthy Attacks on Autonomous Robotic...

Pritam Dash, Mehdi Karimibiuki, and Karthik Pattabiraman (University of British Columbia)

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Demo #1: Curricular Reinforcement Learning for Robust Policy in...

Yunzhe Tian, Yike Li, Yingxiao Xiang, Wenjia Niu, Endong Tong, and Jiqiang Liu (Beijing Jiaotong University)

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Detecting CAN Masquerade Attacks with Signal Clustering Similarity

Pablo Moriano (Oak Ridge National Laboratory), Robert A. Bridges (Oak Ridge National Laboratory) and Michael D. Iannacone (Oak Ridge National Laboratory)

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