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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Demo #14: In-Vehicle Communication Using Named Data Networking

Zachariah Threet (Tennessee Tech), Christos Papadopoulos (University of Memphis), Proyash Poddar (Florida International University), Alex Afanasyev (Florida International University), William Lambert (Tennessee Tech), Haley Burnell (Tennessee Tech), Sheikh Ghafoor (Tennessee Tech) and Susmit Shannigrahi (Tennessee Tech)

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Chosen-Instruction Attack Against Commercial Code Virtualization Obfuscators

Shijia Li (College of Computer Science, NanKai University and the Tianjin Key Laboratory of Network and Data Security Technology), Chunfu Jia (College of Computer Science, NanKai University and the Tianjin Key Laboratory of Network and Data Security Technology), Pengda Qiu (College of Computer Science, NanKai University and the Tianjin Key Laboratory of Network and Data…

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RamBoAttack: A Robust and Query Efficient Deep Neural Network...

Viet Quoc Vo (The University of Adelaide), Ehsan Abbasnejad (The University of Adelaide), Damith C. Ranasinghe (University of Adelaide)

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