Practical anomaly detection based on classifying frequent traffic patterns

  title={Practical anomaly detection based on classifying frequent traffic patterns},
  author={Ignasi Paredes-Oliva and Ismael Castell-Uroz and Pere Barlet-Ros and Xenofontas A. Dimitropoulos and Josep Sol{\'e}-Pareta},
  journal={2012 Proceedings IEEE INFOCOM Workshops},
Detecting network traffic anomalies is crucial for network operators as it helps to identify security incidents and to monitor the availability of networked services. Although anomaly detection has received significant attention in the literature, the automatic classification of network anomalies still remains an open problem. In this paper, we introduce a novel scheme and build a system to detect and classify anomalies that is based on an elegant combination of frequent item-set mining with… CONTINUE READING
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