IMPROVED PERFORMANCE OF INTRUSION DETECTION SYSTEM USING FEATURE REDUCTION AND J48 DECISION TREE CLASSIFICATION ALGORITHM

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dc.contributor.authorAbikoye, Oluwakemi Christianah
dc.contributor.authorBalogun, Abdullateef Oluwagbemiga
dc.contributor.authorOlarewaju, A. K.
dc.contributor.authorBajeh, Amos Orenyi
dc.date.accessioned2018-05-23T10:36:22Z
dc.date.available2018-05-23T10:36:22Z
dc.date.issued2016
dc.description.abstractDue to the obvious importance of accuracy in the performance of intrusion detection system, in addition to the algorithms used there is an increasing need for more activities to be carried out, aiming for improved accuracy and reduced real time used in detection. This paper investigates the use of filtered dataset on the performance of J48 Decision Tree classifier in its classification of a connection as either normal or an attack. The reduced dataset is based on using Gain Ratio attribute evaluation technique (entropy) for performing feature selection (removal of redundant attributes) and feeding the filtered dataset into a J48 Decision Tree algorithm for classification. A 10-fold cross validation technique was used for the performance evaluation of the J48 Decision Tree classifier on the KDD cup 1999 dataset and simulated in WEKA tool. The results showed J48 decision tree algorithm performed better in terms of accuracy and false positive report on the reduced dataset than the full dataset(Probing full dataset: 97.8%, Probing reduced dataset: 99.5%, U2R full dataset: 75%, reduced dataset: 76.9%, R2L full dataset: 98.0%, reduced dataset: 98.3%).en_US
dc.identifier.citation12. Abikoye, O.C., Balogun, A.O., Olanrewaju, A.K. & Bajeh, A.O. (2016): Improved Performance of Intrusion Detection System using feature Reduction and J48 Decision Tree Classification. Ilorin Journal of Computer Science and Information Technology. Vol 1 No 1. Pp 71-88.en_US
dc.identifier.urihttp://hdl.handle.net/123456789/263
dc.language.isoenen_US
dc.publisherDepartment of Computer Science, Facutly of Communication and Information Sciences, University of Ilorin Ilorin, Nigeria.en_US
dc.relation.ispartofseriesVolume: 1;Issue: 1
dc.subjectMachine Learningen_US
dc.subjectData Miningen_US
dc.subjectNetwork securityen_US
dc.subjectIntrusion Detection Systemen_US
dc.titleIMPROVED PERFORMANCE OF INTRUSION DETECTION SYSTEM USING FEATURE REDUCTION AND J48 DECISION TREE CLASSIFICATION ALGORITHMen_US
dc.typeArticleen_US

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