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Applied Computational Intelligence and Soft Computing
Volume 2012 (2012), Article ID 850160, 20 pages
http://dx.doi.org/10.1155/2012/850160
Review Article

The Use of Artificial-Intelligence-Based Ensembles for Intrusion Detection: A Review

1Department of Computer Application, Shaheed Bhagat Singh State Technical Campus, Ferozepur, Punjab 152004, India
2Department of Computer Science & Engineering, Punjab Institute of Technology, Kapurthala, Punjab 144601, India

Received 4 April 2012; Accepted 11 July 2012

Academic Editor: Farid Melgani

Copyright © 2012 Gulshan Kumar and Krishan Kumar. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

In supervised learning-based classification, ensembles have been successfully employed to different application domains. In the literature, many researchers have proposed different ensembles by considering different combination methods, training datasets, base classifiers, and many other factors. Artificial-intelligence-(AI-) based techniques play prominent role in development of ensemble for intrusion detection (ID) and have many benefits over other techniques. However, there is no comprehensive review of ensembles in general and AI-based ensembles for ID to examine and understand their current research status to solve the ID problem. Here, an updated review of ensembles and their taxonomies has been presented in general. The paper also presents the updated review of various AI-based ensembles for ID (in particular) during last decade. The related studies of AI-based ensembles are compared by set of evaluation metrics driven from (1) architecture & approach followed; (2) different methods utilized in different phases of ensemble learning; (3) other measures used to evaluate classification performance of the ensembles. The paper also provides the future directions of the research in this area. The paper will help the better understanding of different directions in which research of ensembles has been done in general and specifically: field of intrusion detection systems (IDSs).