Wu, Yingwen

AnomalyAID: Reliable Interpretation for Semi-supervised Network Anomaly Detection

2024 · arXiv (Cornell University)

Semi-supervised Learning plays a crucial role in network anomaly detection applications, however, learning anomaly patterns with limited labeled samples is not easy. Additionally, the lack of interpretability creates key barriers to the adoption of semi-supervised …