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The popularization of shared networks and Internet usage demands increases attention on information system security, particularly on intrusion detection. Intrusion detection in the internet is an active area of research. In this paper, the authors apply one of the efficient data mining algorithms called Support Vector Machines (SVM) for network intrusion detection. Experimental results on the KDD cup'99 data set show the novelty of their approach in detecting network intrusion. It is observed that the proposed technique performs better in terms of false positive rate, cost, and computational time when applied to KDD'99 data sets compared to a back propagation neural network based approach.
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