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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HeadStart: Efficiently Verifiable and Low-Latency Participatory Randomness Generation at...

Hsun Lee (National Taiwan University), Yuming Hsu (National Taiwan University), Jing-Jie Wang (National Taiwan University), Hao Cheng Yang (National Taiwan University), Yu-Heng Chen (National Taiwan University), Yih-Chun Hu (University of Illinois at Urbana-Champaign), Hsu-Chun Hsiao (National Taiwan University)

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Testability Tarpits: the Impact of Code Patterns on the...

Feras Al Kassar (SAP Security Research), Giulia Clerici (SAP Security Research), Luca Compagna (SAP Security Research), Davide Balzarotti (EURECOM), Fabian Yamaguchi (ShiftLeft Inc)

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Generation of CAN-based Wheel Lockup Attacks on the Dynamics...

Alireza Mohammadi (University of Michigan-Dearborn), Hafiz Malik (University of Michigan-Dearborn) and Masoud Abbaszadeh (GE Global Research)

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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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