Time Matters: Temporal NetFlow Features for ML-Based Network Intrusion Detection
The results demonstrate that augmenting conventional flow features with temporal information yields consistent gains; binary detection improves by up to 3% in F1 score, while macro-averaged multi-class F1 increases by approximately 27%, with the most significant improvements occurring in attack classes with pronounced temporal signatures.
Majed Luay, S. Layeghy, Niloufar Noorbin et al.
· IEEE Access · 21 citations