Abstract
Intruders attack both commercial and corporate distributed systems successfully. The problem of intruders has become vital. The most effective resistance today is the use of Intrusion Detection Systems. An intrusion detection system analysis all aspects of network activities in order to identify the existence of unusual patterns that may represent a network or system attack made by intruders attempting to compromise a system. This paper brings an idea of applying data mining algorithms to the intrusion detection system. Performance of various tree based classifiers like Decision Stump, BF Tree, ID3, J48, LAD, Random Tree, REP Tree, Random Forest and Simple Cart algorithms are compared and the experimental study shows that the Random Forest algorithm outperforms than other algorithms in terms of accuracy, specificity and sensitivity and Time.
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Nadiammai, G.V., Hemalatha, M. (2013). Performance Analysis of Tree Based Classification Algorithms for Intrusion Detection System. In: Prasath, R., Kathirvalavakumar, T. (eds) Mining Intelligence and Knowledge Exploration. Lecture Notes in Computer Science(), vol 8284. Springer, Cham. https://doi.org/10.1007/978-3-319-03844-5_9
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DOI: https://doi.org/10.1007/978-3-319-03844-5_9
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-03843-8
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