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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A Lightweight IoT Cryptojacking Detection Mechanism in Heterogeneous Smart...

Ege Tekiner (Florida International University), Abbas Acar (Florida International University), Selcuk Uluagac (Florida International University)

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DRAWN APART: A Device Identification Technique based on Remote...

Tomer Laor (Ben-Gurion Univ. of the Negev), Naif Mehanna (Univ. Lille, CNRS, Inria), Antonin Durey (Univ. Lille, CNRS, Inria), Vitaly Dyadyuk (Ben-Gurion Univ. of the Negev), Pierre Laperdrix (Univ. Lille, CNRS, Inria), Clémentine Maurice (Univ. Lille, CNRS, Inria), Yossi Oren (Ben-Gurion Univ. of the Negev), Romain Rouvoy (Univ. Lille, CNRS, Inria / IUF), Walter Rudametkin…

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DRIVETRUTH: Automated Autonomous Driving Dataset Generation for Security Applications

Raymond Muller (Purdue University), Yanmao Man (University of Arizona), Z. Berkay Celik (Purdue University), Ming Li (University of Arizona) and Ryan Gerdes (Virginia Tech)

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