Network Traffic Anomalies Detection and Identification with Flow Monitoring

Network management and security is currently one of the most vibrant research areas, among which, research on detecting and identifying anomalies has attracted a lot of interest. Researchers are still struggling to find an effective and lightweight method for anomaly detection purpose. In this paper, we propose a simple, robust method that detects network anomalous traffic data based on flow monitoring. Our method works based on monitoring the four predefined metrics that capture the flow statistics of the network. In order to prove the power of the new method, we did build an application that detects network anomalies using our method. And the result of the experiments proves that by using the four simple metrics from the flow data, we do not only effectively detect but can also identify the network traffic anomalies.

• Type: Journal
• Year: 2010
• Where: CORR
• Authors: Huy Anh Nguyen, Tam Van Nguyen, Dong Il Kim, Deokjai Choi
• Keywords: CORR 2010, Education, Network Anomalous Traffic, Network Management, Vibrant Research Areas