Anyalebechi Felicia Nneamaka

Explainable Artificial Intelligence-Based Intrusion Detection for Zero-Day Cyber Attacks: A Hybrid Transformer–Long Short-Term Memory Framework with SHapley Additive exPlanations and Local Interpretable Model-Agnostic Explanations Interpretability

The findings indicate that embedding explainability directly into the zero-day detection pipeline, rather than treating it as an auxiliary diagnostic layer, materially improves both detection robustness and analyst-facing transparency without incurring prohibitive computational overhead.