Gain Ratio and Decision Tree Classifier for Intrusion Detection
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Date
2015
Journal Title
Journal ISSN
Volume Title
Publisher
Foundation of Computer Science (FCS), NY, USA
Abstract
With the evident need for accuracy in the performance of
intrusion detection system, it is expedient that in addition to
the algorithms used, more activities should be carried out to
improve accuracy and reduce real time used in detection. This
paper reviews how data mining relates to IDS, feature
selection and classification. This paper proposes architecture
of IDS where GainRatio is used for feature selection and
decision tree for classification using NSL-KDD99 dataset, It
also includes the evaluation of the performance of the
Decision tree on the dataset and also on the reduced dataset.
Description
Keywords
Machine Learning, Data Mining, Knowledge Discovery, Intrusion Detection System
Citation
18. Mabayoje M.A., Akintola, A. G., Balogun, A. O & Ayilara, O. (2015): Gain Ratio and Decision Tree Classifier for Intrusion Detection. International Journal of Computer Applications (IJCA). 126(1):56-59