MSTE-CAN: Multi-channel Spatial-Temporal Encoding and Coordinate Attention-based ResNet for high-efficiency CAN bus intrusion detection

This research paper presents MSTE-CAN, a deep learning model designed to detect unauthorized access attempts on CAN bus systems (the communication network used in vehicles and industrial equipment). The model uses multi-channel spatial-temporal encoding (a technique that analyzes patterns across multiple data streams over time) and coordinate attention mechanisms (methods that help the AI focus on important parts of the data) combined with ResNet (a type of neural network architecture) to identify intrusions more efficiently than previous approaches.