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.

View More Papers

Stacking up the LLM Risks: Applied Machine Learning Security

Dr. Gary McGraw, Berryville Institute of Machine Learning

Read More

AVMON: Securing Autonomous Vehicles by Learning Control Invariants and...

Ahmed Abdo, Sakib Md Bin Malek, Xuanpeng Zhao, Nael Abu-Ghazaleh (University of California, Riverside)

Read More

Eavesdropping on Black-box Mobile Devices via Audio Amplifier's EMR

Huiling Chen (College of Computer Science and Electronic Engineering, Hunan University, Changsha, China), Wenqiang Jin (College of Computer Science and Electronic Engineering, Hunan University, Changsha, China), Yupeng Hu (College of Computer Science and Electronic Engineering, Hunan University, Changsha, China), Zhenyu Ning (College of Computer Science and Electronic Engineering, Hunan University, Changsha, China), Kenli Li (College…

Read More

Connecting the Dots in the Sky: Website Fingerprinting in...

Prabhjot Singh (University of Waterloo), Diogo Barradas (University of Waterloo), Tariq Elahi (University of Edinburgh), Noura Limam (University of Waterloo)

Read More