Evan Allen (Virginia Tech), Zeb Bowden (Virginia Tech Transportation Institute), J. Scot Ransbottom (Virginia Tech)

Attackers have found numerous vulnerabilities in the Electronic Control Units (ECUs) of modern vehicles, enabling them to stop the car, control its brakes, and take other potentially disruptive actions. Many of these attacks were possible because the vehicles had insecure In-Vehicle Networks (IVNs), where ECUs could send any message to each other. For example, an attacker who compromised an infotainment ECU might be able to send a braking message to a wheel. In this work, we introduce a scheme based on distributed firewalls to block these unauthorized messages according to a set “security policy” defining what transmissions each ECU should be able to send and receive. We leverage the topology of new switched, zonal networks to authenticate messages without cryptography, using Ternary Content Addressable Memory (TCAMs) to enforce the policy at wire-speed. Crucially, our approach minimizes the security burden on edge ECUs and places control in a set of hardened zonal gateways. Through an OMNeT++ simulation of a zonal IVN, we demonstrate that our scheme has much lower overhead than modern cryptography-based approaches and allows for realtime, low-latency (​<0.1 ms) traffic.

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Location Spoofing Attacks on Autonomous Fleets

Jinghan Yang, Andew Estornell, Yevgeniy Vorobeychik (Washington University in St. Louis)

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DynPRE: Protocol Reverse Engineering via Dynamic Inference

Zhengxiong Luo (Tsinghua University), Kai Liang (Central South University), Yanyang Zhao (Tsinghua University), Feifan Wu (Tsinghua University), Junze Yu (Tsinghua University), Heyuan Shi (Central South University), Yu Jiang (Tsinghua University)

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Lightning Community Shout-Outs to:

(1) Jonathan Petit, Secure ML Performance Benchmark (Qualcomm) (2) David Balenson, The Road to Future Automotive Research Datasets: PIVOT Project and Community Workshop (USC Information Sciences Institute) (3) Jeremy Daily, CyberX Challenge Events (Colorado State University) (4) Mert D. Pesé, DETROIT: Data Collection, Translation and Sharing for Rapid Vehicular App Development (Clemson University) (5) Ning…

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