A Real-Time Approach to Autonomous CAN Bus Reverse Engineering

TL;DR

This paper presents a scalable, real-time method for reverse engineering vehicle CAN bus systems using inertial and CAN data, enabling quick identification of key channels without prior vehicle knowledge.

Contribution

The work introduces a novel real-time approach combining IMU and CAN data for vehicle CAN bus reverse engineering without prior vehicle information.

Findings

Accurately identified CAN channels for vehicle controls

Reduced processing time and computational requirements

Validated method with real vehicle data and previous datasets

Abstract

This paper introduces a real-time method for reverse engineering a vehicle's CAN bus without prior knowledge of the vehicle or its CAN system. By comparing inertial measurement and CAN data during significant vehicle events, the method accurately identified the CAN channels associated with the accelerator pedal, brake pedal, and steering wheel. Utilizing an IMU, CAN module, and event-driven software architecture, the system was validated using prerecorded serialized data from previous studies. This data, collected during multiple vehicle drives, included synchronized IMU and CAN recordings. By using these consistent datasets, the improvements made in this work were tested and validated under the same conditions as in the previous studies, enabling direct comparison to earlier results. Faster processing times were produced and less computational power was needed, as compared to the earlier methods. This work could have potential application to making aftermarket autonomous vehicle kits and for cybersecurity applications. It is a scalable and adaptable solution for autonomous CAN reverse engineering in near real-time.