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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Shihong Huang (University of Michigan, Ann Arbor), Yiheng Feng (Purdue University), Wai Wong (University of Michigan, Ann Arbor), Qi Alfred Chen (UC Irvine), Z. Morley Mao and Henry X. Liu (University of Michigan, Ann Arbor) Best Paper Award Runner-up ($200 cash prize)!

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Repttack: Exploiting Cloud Schedulers to Guide Co-Location Attacks

Chongzhou Fang (University of California, Davis), Han Wang (University of California, Davis), Najmeh Nazari (University of California, Davis), Behnam Omidi (George Mason University), Avesta Sasan (University of California, Davis), Khaled N. Khasawneh (George Mason University), Setareh Rafatirad (University of California, Davis), Houman Homayoun (University of California, Davis)

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An In-Depth Analysis on Adoption of Attack Mitigations in...

Ruotong Yu (Stevens Institute of Technology, University of Utah), Yuchen Zhang, Shan Huang (Stevens Institute of Technology)

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