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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Free Proxies Unmasked: A Vulnerability and Longitudinal Analysis of...

Naif Mehanna (Univ. Lille / Inria / CNRS), Walter Rudametkin (IRISA / Univ Rennes), Pierre Laperdrix (CNRS, Univ Lille, Inria Lille), and Antoine Vastel (Datadome)

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CAGE: Complementing Arm CCA with GPU Extensions

Chenxu Wang (Southern University of Science and Technology (SUSTech) and The Hong Kong Polytechnic University), Fengwei Zhang (Southern University of Science and Technology (SUSTech)), Yunjie Deng (Southern University of Science and Technology (SUSTech)), Kevin Leach (Vanderbilt University), Jiannong Cao (The Hong Kong Polytechnic University), Zhenyu Ning (Hunan University), Shoumeng Yan (Ant Group), Zhengyu He (Ant…

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SLMIA-SR: Speaker-Level Membership Inference Attacks against Speaker Recognition Systems

Guangke Chen (ShanghaiTech University), Yedi Zhang (National University of Singapore), Fu Song (Institute of Software, Chinese Academy of Sciences; University of Chinese Academy of Sciences)

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