Unsupervised Time Series Extraction from Controller Area Network Payloads

Authors

Brent C. Stone, Air Force Institute of Technology
Scott R. Graham, Air Force Institute of TechnologyFollow
Barry E. Mullins, Air Force Institute of TechnologyFollow
Christine M. Schubert Kabban, Air Force Institute of TechnologyFollow

Document Type

Conference Proceeding

Publication Date

Fall 2018

Abstract

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.

Comments

Copyright statement: ©2018 IEEE

The "Link to Full Text" on this page loads the arXiv e-print of the conference paper, hosted at the arXiv repository. arXiv:1904.03078 [cs.CR]

The version of record for the conference paper is cited below, and accessible through a subscription to IEEE through the DOI link below.

DOI

10.1109/VTCFall.2018.8690615

Source Publication

2018 IEEE 88th Vehicular Technology Conference (VTC-Fall)

Recommended Citation

B. C. Nolan, S. Graham, B. Mullins and C. S. Kabban, "Unsupervised Time Series Extraction from Controller Area Network Payloads," 2018 IEEE 88th Vehicular Technology Conference (VTC-Fall), 2018, pp. 1-5, doi: 10.1109/VTCFall.2018.8690615.