Zainal, Anazida and Maarof, Mohd Aizaini and Shamsuddin, Siti Mariyam (2006) Feature Selection Using Rough Set in Intrusion Detection. In: IEEE TENCON 2006, 14-17th November 2006, Hongkong.
Most of existing Intrusion Detection Systems use all data features to detect an intrusion. Very little works address the importance of having a small feature subset in designing an efficient intrusion detection system. Some features are redundant and some contribute little to the intrusion detection process. The purpose of this study is to investigate the effectiveness of Rough Set Theory in identifying important features in building an intrusion detection system. Rough Set was also used to classify the data. Here, we used KDD Cup 99 data. Empirical results indicate that Rough Set is comparable to other feature selection techniques deployed by few other researchers.
|Item Type:||Conference or Workshop Item (Paper)|
|Uncontrolled Keywords:||Intrusion Detection, feature selection, Rough Set Theory|
|Subjects:||Q Science > QA Mathematics > QA75 Electronic computers. Computer science|
|Divisions:||Computer Science and Information System (Formerly known)|
|Deposited By:||Anazida Zainal|
|Deposited On:||21 May 2007 08:12|
|Last Modified:||01 Jun 2010 03:08|
Repository Staff Only: item control page