Abstract
Automatic discovery of network applications is a very challenging task which has received a lot of attentions due to its importance in many areas such as network security, QoS provisioning, and network management. In this paper, we propose an online hybrid mechanism for the classification of network flows, in which we employ a signature-based classifier in the first level, and then using the weighted unigram model we improve the performance of the system by labeling the unknown portion. Our evaluation on two real networks shows between 5% and 9% performance improvement applying the genetic algorithm based scheme to find the appropriate weights for the unigram model.
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References
Quinlan, J.: C4.5: Programs for Machine Learning. Morgan Kaufmann, San Francisco (1993)
Moore, D., Keys, K., Koga, R., Lagache, E., Claffy, K.: The CoralReef Software Suite as a Tool for System and Network Administrators. In: Proceedings of the 15th USENIX conference on System administration, pp. 133–144 (2001)
Gummadi, K., Dunn, R., Saroiu, S., Gribble, S., Levy, H., Zahorjan, J.: Measurement, modeling, and analysis of a peer-to-peer file-sharing workload. ACM SIGOPS Operating Systems Review 37(5), 314–329 (2003)
Sen, S., Wang, J.: Analyzing peer-to-peer traffic across large networks. In: Proceedings of the 2nd ACM SIGCOMM Workshop on Internet measurment, pp. 137–150 (2002)
Sen, S., Spatscheck, O., Wang, D.: Accurate, scalable in-network identification of p2p traffic using application signatures. In: Proceedings of the 13th international conference on World Wide Web, pp. 512–521 (2004)
Hall, M., Frank, E., Holmes, G., Pfahringer, B., Reutemann, P., Witten, I.: The WEKA Data Mining Software: An Update. SIGKDD Explorations 11(1) (2009)
Meffert, K., Rotstan, N., Knowles, C., Sangiorgi, U.: JGAP–Java Genetic Algorithms and Genetic Programming Package, http://jgap.sf.net
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Tavallaee, M., Lu, W., Bagheri, E., Ghorbani, A.A. (2010). Automatic Discovery of Network Applications: A Hybrid Approach. In: Farzindar, A., Kešelj, V. (eds) Advances in Artificial Intelligence. Canadian AI 2010. Lecture Notes in Computer Science(), vol 6085. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-13059-5_21
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DOI: https://doi.org/10.1007/978-3-642-13059-5_21
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-13058-8
Online ISBN: 978-3-642-13059-5
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