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.

View More Papers

(Short) WIP: End-to-End Analysis of Adversarial Attacks to Automated...

Hengyi Liang, Ruochen Jiao (Northwestern University), Takami Sato, Junjie Shen, Qi Alfred Chen (UC Irvine), and Qi Zhu (Northwestern University) Best Short Paper Award Winner!

Read More

Local and Central Differential Privacy for Robustness and Privacy...

Mohammad Naseri (University College London), Jamie Hayes (DeepMind), Emiliano De Cristofaro (University College London & Alan Turing Institute)

Read More

SemperFi: Anti-spoofing GPS Receiver for UAVs

Harshad Sathaye (Northeastern University), Gerald LaMountain (Northeastern University), Pau Closas (Northeastern University), Aanjhan Ranganathan (Northeastern University)

Read More

The Inconvenient Truths of Ground Truth for Binary Analysis

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

Read More