Machine Learning-Based Network Intrusion Detection System: A Dual-Pipeline Approach with Explainable AI and Multi-Model Integration
Traditional Network Intrusion Detection Systems (NIDS) usually have high false-positive rates, low interpretability, and inefficiency in detecting offensive attack patterns in real-time. This paper will describe a dual-pipeline NID architecture which combines ensemble machine learning and hybrid deep learning models to...