Jake Jepson, Rik Chatterjee, Jeremy Daily (Colorado State University)

ETAS Best Paper Award Runner-up!

In compliance with U.S. regulations, modern commercial trucks are required by law to be equipped with Electronic Logging Devices (ELDs), which have become potential cybersecurity threat vectors. Our research uncovers three critical vulnerabilities in commonly used ELDs.

First, we demonstrate that these devices can be wirelessly controlled to send arbitrary Controller Area Network (CAN) messages, enabling unauthorized control over vehicle systems. The second vulnerability demonstrates malicious firmware can be uploaded to these ELDs, allowing attackers to manipulate data and vehicle operations arbitrarily. The final vulnerability, and perhaps the most concerning, is the potential for a selfpropagating truck-to-truck worm, which takes advantage of the inherent networked nature of these devices. Such an attack could lead to widespread disruptions in commercial fleets, with severe safety and operational implications. For the purpose of demonstration, bench level testing systems were utilized. Additional testing was conducted on a 2014 Kenworth T270 Class 6 research truck with a connected vulnerable ELD.

These findings highlight an urgent need to improve the security posture in ELD systems. Following some existing best practices and adhering to known requirements can greatly improve the security of these systems. The process of discovering the vulnerabilities and exploiting them is explained in detail. Product designers, programmers, engineers, and consumers should use this information to raise awareness of these vulnerabilities and encourage the development of safer devices that connect to vehicular networks.

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Phillip Rieger (Technical University of Darmstadt), Torsten Krauß (University of Würzburg), Markus Miettinen (Technical University of Darmstadt), Alexandra Dmitrienko (University of Würzburg), Ahmad-Reza Sadeghi (Technical University of Darmstadt)

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Rao Li (The Pennsylvania State University), Shih-Chieh Dai (Pennsylvania State University), Aiping Xiong (Penn State University)

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WIP: Hidden Hub Eavesdropping Attack in Matter-enabled Smart Home...

Song Liao, Jingwen Yan, Long Cheng (Clemson 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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