Abstract
Modern vehicles communicate internally over the Controller Area Network (CAN) bus, but each manufacturer uses proprietary, undocumented message formats. This opacity prevents researchers, security auditors, and third-party app developers from interpreting the rich data flowing through a vehicle's nervous system.
LibreCAN is an automated CAN message translation system that reverse-engineers the meaning of CAN signals without access to manufacturer databases. By correlating CAN traffic with known physical signals (OBD-II diagnostics, GPS, and inertial sensors), LibreCAN automatically identifies and labels signals for speed, RPM, steering angle, and dozens of other quantities — making vehicular data transparent to developers and security researchers.
Key Contributions
- Automated reverse-engineering of proprietary CAN message formats across vehicle brands.
- Correlation-based approach requires no manufacturer database or prior knowledge.
- Enables security research, intrusion detection, and app development on any vehicle.
- Open-source tool used widely by the automotive security research community.
BibTeX
@inproceedings{pese2019librecan,
title = {LibreCAN: Automated CAN Message Translator},
author = {Pes\'{e}, Mert D. and Stacer, Troy and Campos, C. Andr\'{e}s and Newberry, Eric and Chen, Dongyao and Shin, Kang G.},
booktitle = {Proceedings of the 2019 ACM SIGSAC Conference on Computer and Communications Security (CCS)},
year = {2019},
publisher = {ACM}
}