Building Recommender Systems for Network Intrusion Detection Using Intelligent Decision Technologies

Abstract

This chapter presents an overview of the field of recommender systems and describes the current generation of recommendation methods with their limitations and possible extensions that can improve the capabilities of the recommendations made suitable for a wide range of applications. In recent years, machine learning algorithms have been considered to be an important part of the recommendation process to take intelligent decisions. The chapter will explore the application of such techniques in the field of network intrusion detection in order to examine the vulnerabilities of different recommendation techniques. Finally, the authors outline some of the major issues in building secure recommendation systems in identifying possible network intrusions.