This paper introduces a method for unsupervised tokenization of Controller Area Network (CAN) data payloads using bit level transition analysis and a greedy grouping strategy. The primary goal of this proposal is to extract individual time series which have been concatenated together before transmission onto a vehicle's CAN bus. This process is necessary because the documentation for how to properly extract data from a network may not always be available; passenger vehicle CAN configurations are protected as trade secrets. At least one major manufacturer has also been found to deliberately misconfigure their documented extraction methods. Thus, this proposal serves as a critical enabler for robust third-party security auditing and intrusion detection systems which do not rely on manufacturers sharing confidential information.
Cite
@article{arxiv.1904.03078,
title = {Unsupervised Time Series Extraction from Controller Area Network Payloads},
author = {Brent J. Stone and Scott Graham and Barry Mullins and Christine Schubert Kabban},
journal= {arXiv preprint arXiv:1904.03078},
year = {2019}
}