Details

Autor(en) / Beteiligte

• Rung-Ching Chen
• Kai-Fan Cheng
• Ying-Hao Chen
• Chia-Fen Hsieh

Titel

Using Rough Set and Support Vector Machine for Network Intrusion Detection System

Ist Teil von

• 2009 First Asian Conference on Intelligent Information and Database Systems, 2009, p.465-470

Ort / Verlag

IEEE

Erscheinungsjahr

2009

Quelle

IEEE Electronic Library Online

Beschreibungen/Notizen

• 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 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.