Jose A. Onieva

Towards maintainable AI-driven network anomaly and threat detection: a comparative analysis of datasets, preprocessing techniques, and model trade-offs

A comparative experimental study of anomaly and threat detection techniques used in network analysis through a multistep pipeline, demonstrating that hybrid architectures achieve superior generalisation, yet face challenges regarding computational overhead and cross-dataset adaptability.