Traffic classification using a statistical approach

  • Authors:
  • Denis Zuev;Andrew W. Moore

  • Affiliations:
  • Mathematical Institute, University of Oxford;Computer Laboratory, University of Cambridge

  • Venue:
  • PAM'05 Proceedings of the 6th international conference on Passive and Active Network Measurement
  • Year:
  • 2005

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Abstract

Accurate traffic classification is the keystone of numerous network activities. Our work capitalises on hand-classified network data, used as input to a supervised Bayes estimator. We illustrate the high level of accuracy achieved with a supervised Naïve Bayes estimator; with the simplest estimator we are able to achieve better than 83% accuracy on both a per-byte and a per-packet basis.