A novel intrusion detection system based on hierarchical clustering and support vector machines
Expert Systems with Applications: An International Journal
Mutual information-based feature selection for intrusion detection systems
Journal of Network and Computer Applications
Towards a multiagent-based distributed intrusion detection system using data mining approaches
ADMI'11 Proceedings of the 7th international conference on Agents and Data Mining Interaction
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In Intrusion Detection Systems, many intelligent information processing methods, data miming technology and so on have been applied to generating attack signatures automatically, updating signatures easily and improving detection accuracy with ultra data set. This paper presents an improved association rule discovering system under rough set theory framework of modeling IDSs. The system makes association rule applicable in classifying fields. The system exploits data reductions, rule selection, feature selection to improve detection accuracy and reduce false alarm and unreal alarm. Empirical results illustrate that the intrusion detection model can detect intrusion accurately.