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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(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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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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WIP: Interrupt Attack on TEE-protected Robotic Vehicles

Mulong Luo (Cornell University) and G. Edward Suh (Cornell University)

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FitM: Binary-Only Coverage-GuidedFuzzing for Stateful Network Protocols

Dominik Maier, Otto Bittner, Marc Munier, Julian Beier (TU Berlin)

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