Publication Details

Abstract

Explainable Artificial Intelligence (XAI) improves cybersecurity risk assessment and threat classification by making sophisticated machine learning models more transparent, interpretable, and reliable. Traditional AI-driven security solutions are generally "black boxes," making decision-making difficult and preventing effective threat response. XAI helps security specialists understand why certain behaviours are hazardous or benign by offering explicit insights into model behaviour, feature importance, and decision-making processes. Improved interpretability improves threat detection, incident response, regulatory compliance, and human-machine collaboration. Explainability can help organisations build more dependable, responsible, and resilient cybersecurity systems that respond to changing cyber threats while maintaining user confidence and operational transparency.