AI RESEARCH
ExAI5G: A Logic-Based Explainable AI Framework for Intrusion Detection in 5G Networks
arXiv CS.LG
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ArXi:2604.18052v1 Announce Type: cross Intrusion detection systems (IDSs) for 5G networks must handle complex, high-volume traffic. Although opaque "black-box" models can achieve high accuracy, their lack of transparency hinders trust and effective operational response. We propose ExAI5G, a framework that prioritizes interpretability by integrating a Transformer-based deep learning IDS with logic-based explainable AI (XAI) techniques. The framework uses Integrated Gradients to attribute feature importance and extracts a surrogate decision tree to derive logical rules. We.