Statistical Traffic Anomaly Detection in Time-Varying Communication Networks

  title={Statistical Traffic Anomaly Detection in Time-Varying Communication Networks},
  author={Jing Wang and Ioannis Ch. Paschalidis},
  journal={IEEE Transactions on Control of Network Systems},
We propose two methods for traffic anomaly detection in communication networks where properties of normal traffic evolve dynamically. We formulate the anomaly detection problem as a binary composite hypothesis testing problem and develop a model-free and a model-based method, leveraging techniques from the theory of large deviations. Both methods first extract a family of probability laws (PLs) that represent normal traffic patterns during different time-periods, and then detect anomalies by… CONTINUE READING
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