Using a behaviour knowledge space approach for detecting unknown IP traffic flows

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 6713 LNCS, Issue , 2011, Pages 360-369

  Dainotti, Alberto ^a   Pescapé, Antonio ^a   Sansone, Carlo ^a   Quintavalle, Antonio ^a  

^a UNIVERSITY OF NAPLES FEDERICO II   (Italy)

Author keywords

[No Author keywords available]

Indexed keywords

EXPERIMENTAL EVALUATION; IP FLOW; IP TRAFFIC FLOWS; KNOWLEDGE SPACES; MANAGEMENT PLATFORMS; MULTIPLE CLASSIFIER APPROACH; NETWORK SCENARIO; REAL TRAFFIC; UNKNOWN CLASS;

NETWORK MANAGEMENT; NETWORK PROTOCOLS;

INTERNET PROTOCOLS;

EID: 80053001326     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-21557-5_38     Document Type: Conference Paper

References (23)

1. L7-filter, Application Layer Packet Classifier for Linux, http://l7-filter.sourceforge.net
2. Aceto, G., Dainotti, A., de Donato, W., Pescapé, A.: PortLoad: taking the best of two worlds in traffic classification. In: IEEE INFOCOM 2010 - WiP Track (March 2010)
3. Alshammari, R., Zincir-Heywood, A.N.: Machine learning based encrypted traffic classification: identifying ssh and skype. In: CISDA 2009: Proceedings of the Second IEEE international conference on Computational intelligence for security and defense applications, USA, pp. 289-296. IEEE Press, Piscataway (2009)
4. Auld, T., Moore, A.W., Gull, S.F.: Bayesian neural networks for internet traffic classification. IEEE Transactions on Neural Networks 18(1), 223-239 (2007)
5. Bernaille, L., Teixeira, R.: Early recognition of encrypted applications. In: PAM, pp. 165-175 (2007)
6. Callado, A., Kelner, J., Sadok, D., Kamienski, C.A., Fernandes, S.: Better network traffic identification through the independent combination of techniques. Journal of Network and Computer Applications 33(4), 433-446 (2010)
7. Callado, A., Szabó, C.K.G., Gero, B.P., Kelner, J., Fernandes, S., Sadok, D.: A Survey on Internet Traffic Identification. IEEE Communications Surveys & Tutorials 11(3) ( July 2009)
8. Corona, I., Giacinto, G., Mazzariello, C., Roli, F., Sansone, C.: Information fusion for computer security: State of the art and open issues. Information Fusion 10(4), 274-284 (2009)
9. Dainotti, A., de Donato, W., Pescapè, A.: Tie: A community-oriented traffic classification platform. In: TMA pp. 64-74 (2009)
10. Dainotti, A., de Donato, W., Pescapè, A., Ventre, G.: Tie: A community-oriented traffic classification platform. Technical Report TR-DIS-102008-TIE, Dipartimento di Informatica e Sistemistica, Universitá degli Studi di Napoli Federico II (October 2008)
11. Dainotti, A., Pescapè, A., Sansone, C.: Early classification of network traffic through multi-classification. In: TMA - Traffic Monitoring and Analysis Workshop ( in Press 2011)
12. Dainotti, A., Pescapè, A., Ventre, G.: A packet-level characterization of network traffic. In: CAMAD, pp. 38-45. IEEE, Los Alamitos (2006)
13. He, H., Che, C., Ma, F., Zhang, J., Luo, X.: Traffic classification using en-semble learning and co-training. In: AIC 2008: Proceedings of the 8th conference on Applied informatics and communications, pp. 458-463. World Scientific and Engineering Academy and Society (WSEAS), Wisconsin (2008)
14. Huang, Y.S., Suen, C.Y.: A method of combining multiple experts for the recognition of unconstrained handwritten numerals. IEEE Trans. Pattern Analysis and Machine Intelligence 17(1), 90-94 (1995)
15. Kim, H., Claffy, K., Fomenkov, M., Barman, D., Faloutsos, M., Lee, K.: Internet traffic classification demystified: myths, caveats, and the best practices. In: CoNEXT 2008: Proceedings of the 2008 ACM CoNEXT Conference, pp. 1-12. ACM Press, New York (2008)
16. Kuncheva, L.I.: Combining Pattern Classifiers: Methods and Algorithms. Wiley Interscience, Hoboken (2004)
17. Kuncheva, L.I., Bezdek, J.C., Duin, R.P.W.: Decision templates for multiple classifier fusion: an experimental comparison. Pattern Recognition 34(2), 299-314 (2001)
18. Nguyen, T.T., Armitage, G.: A Survey of Techniques for Internet Traffic Classification using Machine Learning. IEEE Communications Surveys and Tutorials (2008)
19. Park, J., Tyan, H.R., Kuo, C.C.J.: Ga-based internet traffic classification technique for qos provisioning. Intelligent Information Hiding and Multimedia Signal Processing, International Conference on 0, 251-254 (2006)
20. Szabo, G., Szabo, I., Orincsay, D.: Accurate traffic classification, jun. 2007, pp. 1-8 (2007)
21. Williams, N., Zander, S., Armitage, G.: Evaluating machine learning algorithms for automated network application identification. In: Tech. Rep. 060401B, CAIA, April 2006, Swinburne Univ. (2006)
22. Williams, N., Zander, S., Armitage, G.: A preliminary performance comparison of five machine learning algorithms for practical ip traffic flow classification. ACM SIGCOMM CCR 36(5), 7-15 (2006)
23. Wright, C.V., Monrose, F., Masson, G.M.: On inferring application protocol behaviors in encrypted network traffic. Journal of Machine Learning Research 7, 2745-2769 (December 2006)