An Ensemble Classification Approach for Intrusion Detection

Increased cyber attacks in various forms compel everyone to implement effective intrusion detection systems for protecting their information wealth. From last two decades, there has been extensive research going on in intrusion detection system development using various techniques. But, designing detection systems producing maximum accuracy with minimum false positive is yet a challenging task for the research community. Ensemble method is one of the major developments in the field of machine learning. In this research work, new ensemble classification method is proposed from different classifiers. Support vector machine techniques, artificial neural network and random forest are used for classification. Ensemble model is formed for producing better result. The model shows promising result for all classes of attacks.