Application-based feature selection for internet traffic classification

2010 22nd International Teletraffic Congress - Proceedings, ITC 22

Volumn , Issue , 2010, Pages

  En Najjary, Taoufik ^a   Urvoy Keller, Guillaume ^a   Pietrzyk, Marcin ^b   Costeux, Jean Laurent ^b  

^a EURECOM   (France)

^b ORANGE LABS   (France)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTATION COSTS; EXISTING METHOD; FEATURE SELECTION; FLOW FEATURES; GNUTELLA; HTTP STREAMING; INTERNET TRAFFIC; LOGISTIC REGRESSIONS; NETWORK ADMINISTRATOR; NEW APPROACHES; REAL TIME; RECOGNITION RATES; SELECTION PROCESS; STATISTICAL ALGORITHM; STATISTICAL TECHNIQUES; TRAFFIC CLASSIFICATION;

HTTP; INTERNET SERVICE PROVIDERS; TELECOMMUNICATION TRAFFIC;

FEATURE EXTRACTION;

EID: 78650139732     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ITC.2010.5608734     Document Type: Conference Paper

References (19)

1. RB Bendel and AA. Afifi. Comparison of stopping rules in forward regression. Journal of the American Statistical Association, pages 46-53, 1972.
2. Laurent Bernaille, Renata Teixeira, Universit Pierre, and Marie Curie Lip-cnrs. Early recognition of encrypted applications. In In Passive and Active Measurement conference (PAM 07), 2007.
3. Laurent Bernaille, Renata Teixeira, and Kave Salamatian. Early application identification. In CoNEXT '06: Proceedings of the 2006 ACM CoNEXT conference, pages 1-12, 2006.
4. Jeffrey Erman, Martin Arlitt, and Anirban Mahanti. Traffic classification using clustering algorithms. In MineNet '06: Proceedings of the 2006 SIGCOMM workshop on Mining network data, 2006.
5. James W. Hardin and Joseph W. Hilbe. Generalized Linear Models and Extensions, 2nd Edition. StataCorp LP, 2007.
6. David W. Hosmer and Stanley Leshow. Applied Logistic Regression. New York ; Chichester ; Brisbane : J. Wiley and Sons, cop., 2001.
7. T. Karagiannis, A. Broido, N. Brownlee, K.C. Claffy, and M. Faloutsos. Is p2p dying or just hiding? [p2p traffic measurement]. In Global Telecommunications Conference, 2004. GLOBECOM '04. IEEE, pages 1532-1538 Vol.3, Nov.-3 Dec. 2004. (Pubitemid 40611136)
8. Thomas Karagiannis, Konstantina Papagiannaki, and Michalis Faloutsos. Blinc: multilevel traffic classification in the dark. SIGCOMM Comput. Commun. Rev., 35(4), 2005.
9. Thomas Karagiannis, Konstantina Papagiannaki, Nina Taft, and Michalis Faloutsos. Profiling the end host. In In Passive and Active Measurement conference (PAM 07), April.
10. Hyunchul Kim, KC Claffy, Marina Fomenkov, Dhiman Barman, Michalis Faloutsos, and KiYoung Lee. Internet traffic classification demystified: myths, caveats, and the best practices. In CONEXT '08: Proceedings of the 2008 ACM CoNEXT Conference, pages 1-12, 2008.
11. Wei Li, Marco Canini, Andrew W. Moore, and Raffaele Bolla. Efficient application identification and the temporal and spatial stability of classification schema. Computer Networks, 53(6):790-809, 2009.
12. Andrew W. Moore and Denis Zuev. Internet traffic classification using bayesian analysis techniques. In SIGMETRICS '05: Proceedings of the 2005 ACM SIGMETRICS international conference on Measurement and modeling of computer systems, pages 50-60, 2005. (Pubitemid 43275409)
13. T.T.T. Nguyen and G. Armitage. Training on multiple sub-flows to optimise the use of machine learning classifiers in real-world ip networks. pages 369-376, Nov. 2006.
14. Marcin Pietrzyk, Jean-Laurent Costeux, Taoufik En-Najjary, and Guillaume Urvoy-Keller. Challenging statistical classification for operational usage : the adsl case. In IMC '09: Proceedings of the 9th ACM SIGCOMM conference on Internet measurement, 2009.
15. Marcin Pietrzyk, Guillaume Urvoy-Keller, and Jean-Laurent Costeux. Revealing the unknown adsl traffic using statistical methods. In COST 2009 : Springer : Lecture Notes in Computer Science, Vol 5537, 2009., May 2009.
16. Tstat. http://tstat.tlc.polito.it/.
17. G Armitage TTT Nguyen. A survey of techniques for internet traffic classification using machine learning. Communications Surveys and Tutorials, IEEE, 10(4):56-76, 2008.
18. Jon Tucker and Dr Jon Tucker. Neural networks versus logistic regression in financial modelling: A methodological comparison. In in Proceedings of the 1996 World First Online Workshop on Soft Computing (WSC1, 1996.
19. Jeffery T. Walker and Sean Maddan. Statistics in criminology and criminal justice, Third Edition. Sudbury, Mass., USA, Jones and BartlettPublishers, 2009.