Comparison of Performance for Intrusion Detection System Using Different Rules of Classification [chapter]

Nandita Sengupta, Jaya Sil
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
more » ... on KDD data set where the whole data set is divided into training and test data set. Rules are formed using training data set by different rule generation methods and later applied on test data set to calculate accuracy of classifiers.
doi:10.1007/978-3-642-22786-8_11 fatcat:ymxlwf3gbrhytb73zpuh36hdvu