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Comparison of Performance for Intrusion Detection System Using Different Rules of Classification
[chapter]
2011
Communications in Computer and Information Science
Classification is very important for designing intrusion detection system that classifies network traffic data. Broadly traffic data is classified as normal or anomaly. In the work classification performance using rules obtained by different methods are applied on network traffic and compared. Classifier is built based on rules of decision table, conjunctive rule, OneR, PART, JRip, NNge, ZeroR, BayesNet, Ridor from WEKA and using rough set theory. Classification performance is compared applying
doi:10.1007/978-3-642-22786-8_11
fatcat:ymxlwf3gbrhytb73zpuh36hdvu