Using Rough Set and Support Vector Machine for Network Intrusion Detection

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

2010-04-05

arxiv.org/abs/1004.0567v1

International Journal of Network Security & Its Applications 1.1 (2009) 1-13

Computer Science

Learning

13 Pages

Scientific paper

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.

Affiliated with

Also associated with

No associations

Rating

Using Rough Set and Support Vector Machine for Network Intrusion Detection does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with Using Rough Set and Support Vector Machine for Network Intrusion Detection, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Using Rough Set and Support Vector Machine for Network Intrusion Detection will most certainly appreciate the feedback.

Rate now

Comments { 0 }

Profile ID: LFWR-SCP-O-636804