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| Titel: |
USING ROUGH SET AND SUPPORT VECTOR MACHINE FOR NETWORK INTRUSION DETECTION |
| Auteur: |
Rung-Ching Chen Kai-Fan Cheng Chia-Fen Hsieh |
| Verschenen in: |
International journal of network security & its applications |
| Paginering: | Jaargang 1 (2009) nr. 1 pagina's 01-13 |
| Jaar: |
2009 |
| Inhoud: |
The main function of IDS (Intrusion Detection System) is to protect the system, analyze and predict thebehaviors of users. Then these behaviors will be considered an attack or a normal behavior. Though IDShas been developed for many years, the large number of return alert messages makes managers maintainsystem inefficiently. In this paper, we use RST (Rough Set Theory) and SVM (Support Vector Machine) to detect intrusions. First, RST is used to preprocess the data and reduce the dimensions. Next, the features were selected by RST will be sent to SVM model to learn and test respectively. The method is effective to decrease the space density of data. The experiments will compare the results with different methods and show RST and SVM schema could improve the false positive rate and accuracy |
| Uitgever: |
Academy & Industry Research Collaboration Center (AIRCC) (provided by DOAJ) |
| Bronbestand: |
Elektronische Wetenschappelijke Tijdschriften |
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