Abstract
Detecting distributed anomalies rapidly and accurately is critical for efficient backbone network management. In this letter, we propose a novel anomaly detection method that uses router connection relationships to detect distributed anomalies in the backbone Internet. The proposed method unveils the underlying relationships among abnormal traffic behavior through closed frequent graph mining, which makes the detection effective and scalable.