Mohammed, Muamer N. and Norrozila, Sulaiman and Abdulkarim Muhsin, Osama (2011) A novel Intrusion Detection System by using intelligent data mining in WEKA environment. Procedia Computer Science, 3. pp. 1237-1242. ISSN 1877-0509. (Published)
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Abstract
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.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | Data mining; Intrusion detection system; WEKA |
| Subjects: | Q Science > QA Mathematics > QA76 Computer software |
| Faculty/Division: | Faculty of Computer System And Software Engineering |
| Depositing User: | Mrs. Neng Sury Sulaiman |
| Date Deposited: | 30 May 2019 06:43 |
| Last Modified: | 30 May 2019 06:43 |
| URI: | http://umpir.ump.edu.my/id/eprint/24995 |
| Download Statistic: | View Download Statistics |
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