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CORR
2010
Springer

Using Rough Set and Support Vector Machine for Network Intrusion Detection

11 years 5 months ago
Using Rough Set and Support Vector Machine for Network Intrusion Detection
The main function of IDS (Intrusion Detection System) is to protect the system, analyze and predict the behaviors of users. Then these behaviors will be considered an attack or a normal behavior. Though IDS has been developed for many years, the large number of return alert messages makes managers maintain system 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. KEYWORDS Rough Set; Support Vector Machine; Intrusion Detection System; Attack Detection Rate;
Rung Ching Chen, Kai-Fan Cheng, Chia-Fen Hsieh
Added 09 Dec 2010
Updated 09 Dec 2010
Type Journal
Year 2010
Where CORR
Authors Rung Ching Chen, Kai-Fan Cheng, Chia-Fen Hsieh
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