Unsupervised Time Series Extraction from Controller Area Network Payloads

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.

2018 IEEE 88th Vehicular Technology Conference (VTC2018-Fall)

Cited by in corpus (1)

• Detecting message modification attacks on the CAN bus with Temporal Convolutional Networks