Nowadays, the using of intelligent data mining approaches to predict intrusion in local area networks has been increasing rapidly. In this paper, an improved approach for Intrusion Detection System (IDS) based on combining data mining and expert system is presented and implemented in WEKA. The taxonomy consists of a classification of the detection principle as well as certain WEKA aspects of the intrusion detection system such as open-source data mining. The combining methods may give better performance of IDS systems, and make the detection more effective. The result of the evaluation of the new design produced a better result in terms of detection efficiency and false alarm rate from the existing problems. This presents useful information in intrusion detection.
4th Mosharaka International Conference on Communications, Networking and Information Technology (MIC-CNIT 2010)
Congress
2010 Global Congress on Communications, Networking and Information Technology (GC-CNIT 2010), 3-5 December 2010, Amman, Jordan
Pages
1-4
Topics
Internet Security Optimization of Computing Algorithms
ISSN
2227-331X
DOI
BibTeX
@inproceedings{10CNIT2010,
title={A novel intrusion detection system by using intelligent data mining in WEKA
environment},
author={Muamer Mohammed, and Norrozila Sulaiman, and Osama A. Muhsin},
booktitle={2010 Global Congress on Communications, Networking and Information Technology (GC-CNIT 2010)},
year={2010},
pages={1-4},
doi={}},
organization={Mosharaka for Research and Studies}
}
