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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The Inconvenient Truths of Ground Truth for Binary Analysis

Jim Alves-Foss, Varsha Venugopal (University of Idaho)

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V-Range: Enabling Secure Ranging in 5G Wireless Networks

Mridula Singh (CISPA - Helmholtz Center for Information Security), Marc Roeschlin (ETH Zurich), Aanjhan Ranganathan (Northeastern University), Srdjan Capkun (ETH Zurich)

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(Short) Object Removal Attacks on LiDAR-based 3D Object Detectors

Zhongyuan Hau, Kenneth Co, Soteris Demetriou, and Emil Lupu (Imperial College London) Best Short Paper Award Runner-up!

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SpiralSpy: Exploring a Stealthy and Practical Covert Channel to...

Zhengxiong Li (University at Buffalo, SUNY), Baicheng Chen (University at Buffalo), Xingyu Chen (University at Buffalo), Huining Li (SUNY University at Buffalo), Chenhan Xu (University at Buffalo, SUNY), Feng Lin (Zhejiang University), Chris Xiaoxuan Lu (University of Edinburgh), Kui Ren (Zhejiang University), Wenyao Xu (SUNY Buffalo)

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