Enhanced Features Ranking and Selection Using Recursive Feature Elimination(RFE) and K-Nearest Neighbor Algorithms in Support Vector Machine for Intrusion Detection System
Today, as the increasing the amount of using internet, there are so most information interchanges are performed in that internet. So, the methods used as intrusion detective tools for protecting network systems against diverse attacks are became too important. The available of IDS are getting more powerful. Support Vector Machine was used as the classical pattern reorganization tools have been widely used for Intruder detections. There have some different characteristic of features in building an Intrusion Detection System. Conventional SVM do not concern about that. The authors' enhanced SVM Model proposed with an Recursive Feature Elimination (RFE) and K-Nearest Neighbor (KNN) method to perform a feature ranking and selection task of the new model.