Graph-MRT-LBMNet

Graph-MRT-LBMNet is a physics-inspired graph neural network that combines graph representation learning with Multi-Relaxation-Time (MRT) Lattice Boltzmann dynamics for cybersecurity applications. By integrating graph-based information propagation, MRT collision, and moment-based feature extraction, the architecture effectively captures complex relationships between network connections for accurate intrusion detection. Its scalable and interpretable design provides a robust and efficient framework for detecting cyber threats in modern network environments.