Machine Learning based Research for Network Intrusion Detection: A State-of-the-Art

Abstract

This paper reviews the machine learning based research carried out for  network intrusion detection to lead a secure computer and network systems to the extent possible. Starting with an initial set of about 460 research articles, more than 105 related studies in the period between 2000 and 2013 were selected focusing on using single or combine machine learning techniques for this review. Solutions using convergence of various techniques show a great promise and potential. Related studies are compared by their design, datasets used, and other experimental setups. Current achievements and limitations in developing intrusion detection systems using machine learning techniques are presented and discussed. We assume that reader has aware of basic concepts of machine learning techniques. A good number of future research directions are also provided.