Open access
Aug 2026
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.
Antonio Lara-Gutierrez, Carmen Fernandez-Gago, Jose A. Onieva
· Artificial Intelligence Revi... · 0 citations