skip to main content
article

Traffic classification on the fly

Published:28 April 2006Publication History
Skip Abstract Section

Abstract

The early detection of applications associated with TCP flows is an essential step for network security and traffic engineering. The classic way to identify flows, i.e. looking at port numbers, is not effective anymore. On the other hand, state-of-the-art techniques cannot determine the application before the end of the TCP flow. In this editorial, we propose a technique that relies on the observation of the first five packets of a TCP connection to identify the application. This result opens a range of new possibilities for online traffic classification.

References

  1. T. Karagiannis, A. Broido, N. Brownlee, K. Claffy, and M. Faloutsos, "Is P2P dying or just hiding?," in IEEE Globecom, 2004.Google ScholarGoogle Scholar
  2. M. Roughan, S. Sen, O. Spatscheck, and N. Duffield, "Class-of-service mapping for QoS: A statistical signature-based approach to IP traffic classification," in Internet Measurement Conference, 2004. Google ScholarGoogle ScholarDigital LibraryDigital Library
  3. A. Moore and D. Zuev, "Internet traffic classification using bayesian analysis," in ACM SIGMETRICS, 2005. Google ScholarGoogle ScholarDigital LibraryDigital Library
  4. T. Karagiannis, D. Papagiannaki, and M. Faloutsos, "BLINC: Multilevel traffic classification in the dark," in ACM SIGCOMM, 2005. Google ScholarGoogle ScholarDigital LibraryDigital Library
  5. A. McGregor, M. Hall, P. Lorier, and J. Brunskill, "Flow clustering using machine learning techniques," in Passive and Active Measurement Workshop, 2004.Google ScholarGoogle Scholar
  6. D. Zuev and A. Moore, "Traffic classification using a statistical approach," in Passive and Active Measurement Workshop, 2005. Google ScholarGoogle ScholarDigital LibraryDigital Library
  7. J. McQueen, "Some methods for classification and analysis of multivariations," in Symposium on Mathematical Statistics and Probability, 1967.Google ScholarGoogle Scholar
  8. Qosmos, "www.qosmos.com."Google ScholarGoogle Scholar
  9. Endace, "www.endace.com."Google ScholarGoogle Scholar
  10. N. Hohn and D. Veitch, "Inverting sampled traffic," in Internet Measurement Conference, 2003. Google ScholarGoogle ScholarDigital LibraryDigital Library

Index Terms

  1. Traffic classification on the fly

      Recommendations

      Comments

      Login options

      Check if you have access through your login credentials or your institution to get full access on this article.

      Sign in

      Full Access

      PDF Format

      View or Download as a PDF file.

      PDF

      eReader

      View online with eReader.

      eReader