Anomaly detection using baseline and K-means clustering

@article{Lima2010AnomalyDU,
  title={Anomaly detection using baseline and K-means clustering},
  author={Mois{\'e}s F. Lima and Bruno Bogaz Zarpel{\~a}o and Lucas Dias H. Sampaio and Joel Josx00E9 P. C. Rodrigues and Taufik Abr{\~a}o and Mario Lemes Proença},
  journal={SoftCOM 2010, 18th International Conference on Software, Telecommunications and Computer Networks},
  year={2010},
  pages={305-309}
}
Anomaly detection refers to methods that provide warnings of unusual behaviors which may compromise the security and performance of communication networks. In this paper it is proposed a novel model for network anomaly detection combining baseline, K-means clustering and particle swarm optimization (PSO). The baseline consists of network traffic normal behavior profiles, generated by the application of Baseline for Automatic Backbone Management (BLGBA) model in SNMP historical network data set… CONTINUE READING
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