Mohit Kumar Jangid (Ohio State University) and Zhiqiang Lin (Ohio State University)

Being safer, cleaner, and more efficient, connected and autonomous vehicles (CAVs) are expected to be the dominant vehicles of future transportation systems. However, there are enormous security and privacy challenges while also considering the efficiency and and scalability. One key challenge is how to efficiently authenticate a vehicle in the ad-hoc CAV network and ensure its tamper-resistance, accountability, and non-repudiation. In this paper, we present the design and implementation of Vehicle-to-Vehicle (V2V) protocol by leveraging trusted execution environment (TEE), and show how this TEE-based protocol achieves the objective of authentication, privacy, accountability and revocation as well as the scalability and efficiency. We hope t hat our TEE-based V2V protocol can inspire further research into CAV security and privacy, particularly how to leverage TEE to solve some of the hard problems and make CAV closer to practice.

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Anas Alsoliman, Marco Levorato, and Qi Alfred Chen (UC Irvine)

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PASS: A System-Driven Evaluation Platform for Autonomous Driving Safety...

Zhisheng Hu (Baidu Security), Junjie Shen (UC Irvine), Shengjian Guo (Baidu Security), Xinyang Zhang (Baidu Security), Zhenyu Zhong (Baidu Security), Qi Alfred Chen (UC Irvine) and Kang Li (Baidu Security)

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FedCRI: Federated Mobile Cyber-Risk Intelligence

Hossein Fereidooni (Technical University of Darmstadt), Alexandra Dmitrienko (University of Wuerzburg), Phillip Rieger (Technical University of Darmstadt), Markus Miettinen (Technical University of Darmstadt), Ahmad-Reza Sadeghi (Technical University of Darmstadt), Felix Madlener (KOBIL)

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