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Network traffic anomalies detection and characterization has been a hot topic of research for many years. Although the field is very advanced in the detection of network traffic anomalies, accurate automated classification is still a very challenging and unmet problem. This paper presents a new algorithm for automated classification of network traffic anomalies. The algorithm relies on three steps: (i) after an anomaly has been detected, identify all (or most) related packets or flow records;doi:10.1007/978-3-642-05284-2_6 fatcat:c5echqmsibasdnh377sfewrshm