Ensemble classifiers for network intrusion detection system
Two of the major challenges in designing anomaly intrusion detection are to maximize detection accuracy and to minimize false alarm rate. In addressing this issue, this paper proposes an ensemble of one-class classifiers where each adopts different learning paradigms. The techniques deployed in this...
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| Format: | Article |
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Dynamic Pub.
2009
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