Intrusion Detection Systems: A Survey and Analysis of Classification Techniques

Abstract: Today it is very important to provide a high level security to protect highly sensitive and private information. Intrusion Detection System is an essential technology in Network Security. Nowadays researchers have interested on intrusion detection system using Data mining techniques as an artful skill. IDS is a software or hardware device that deals with attacks by collecting information from a variety of system and network sources, then analyzing symptoms of security problems. This paper includes an overview of intrusion detection systems and introduces the reader to some fundamental concepts of IDS methodology. We also discuss the primary intrusion detection techniques. In this paper, we emphasizes data mining algorithms to implement IDS such as Support Vector Machine, Kernelized support vector machine, Extreme Learning Machine and Kernelized Extreme Learning Machine.

Keywords: SVM, KELM, Intrusion Detection System, Data Mining and IDS, ELM, Classification Techniques for IDS, KSVM