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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Uncovering Cross-Context Inconsistent Access Control Enforcement in Android

Hao Zhou (The Hong Kong Polytechnic University), Haoyu Wang (Beijing University of Posts and Telecommunications), Xiapu Luo (The Hong Kong Polytechnic University), Ting Chen (University of Electronic Science and Technology of China), Yajin Zhou (Zhejiang University), Ting Wang (Pennsylvania State University)

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(Short) Spoofing Mobileye 630’s Video Camera Using a Projector

Ben Nassi, Dudi Nassi, Raz Ben Netanel and Yuval Elovici (Ben-Gurion University of the Negev)

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Demo #2: Policy-based Discovery and Patching of Logic Bugs...

Hyungsub Kim (Purdue University), Muslum Ozgur Ozmen (Purdue University), Antonio Bianchi (Purdue University), Z. Berkay Celik (Purdue University) and Dongyan Xu (Purdue University)

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Context-Sensitive and Directional Concurrency Fuzzing for Data-Race Detection

Zu-Ming Jiang (Tsinghua University), Jia-Ju Bai (Tsinghua University), Kangjie Lu (University of Minnesota), Shi-Min Hu (Tsinghua University)

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