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Zuev D. and Moore A., "Traffic Classification using a Statistical Approach", in Passive and Active Measurement Conference (PAM), Mar 2005.
Traffic Classification using a Statistical Approach
Authors: Zuev D.
Moore A.
Published: Passive and Active Measurement Conference (PAM), 2005
URL:http://www.pamconf.org/2005/PDF/34310324.pdf
Entry Dates: 2009-02-09
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 Naive 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
Results:
  • Genome Campus Datasets;
  • traffic categories: BULK;DATABASE;INTERACTIVE;MAIL;SEVICES;WWW;P2P;ATTACK;GAMES;MULTIMEDIA;
  • demonstrate an accuracy of better than 66% of flows and better than 83% for packets and bytes;
  Last Modified: Tue Oct-8-2019 11:20:58 PDT
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