Conference Proceedings

International Conference on Future Trends In Computing and Communication - FTCC 2013

Accuracy Analysis of Machine Learning Algorithms for Intrusion Detection System using NSL-KDD Dataset

Author(s) : RAGHAVENDRA GANIGA , SANOOP MALLISSERY, SUCHETA KOLEKAR

Abstract

Intrusion Detection System (IDS) that turns to be a vital component to secure the network. The lack of regular updation, less capability to detect unknown attacks, high non adaptable false alarm rate, more consumption of network resources etc., makes IDS to compromise. This paper aims to classify the NSL-KDD dataset with respect to their metric data by using the best six data mining classification algorithms like J48, ID3, CART, Bayes Net, Naïve Bayes and SVM to find which algorithm will be able to offer more testing accuracy. NSL-KDD dataset has solved some of the inherent limitations of the available KDD’99 dataset.

Conference Title : International Conference on Future Trends In Computing and Communication - FTCC 2013
Conference Date(s) : July 13-14, 2013
Place : Hotel Lebua at State Tower, Bangkok
No fo Author(s) : 3
DOI : 10.15224/978-981-07-7021-1-07
Page(s) : 29 - 34
Electronic ISBN : 978-981-07-7021-1
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