Model Based Intrusion Detection using Data Mining Techniques with Feature Reduction

Abstract

The research paper involves model based Intrusion detection through data mining techniques using the NSL-KDD dataset. The approach involves building of classification model and hybrid model which are created using classification techniques and, combining both classification and clustering techniques respectively. Classification model can detect known attacks effectively whereas hybrid models can detect unknown or new attacks also. The comparison of the results of different models is done over different performance evaluation parameters.