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The Scientific World Journal
Volume 2015 (2015), Article ID 314601, 8 pages
Research Article

Fusion of Heterogeneous Intrusion Detection Systems for Network Attack Detection

1Computer Science and Engineering, Kamaraj College of Engineering and Technology, Tamilnadu 626 001, India
2Information Technology, Mepco Schlenk Engineering College, Tamilnadu 626 005, India

Received 31 March 2015; Revised 15 June 2015; Accepted 1 July 2015

Academic Editor: Juan M. Corchado

Copyright © 2015 Jayakumar Kaliappan et al. 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.


An intrusion detection system (IDS) helps to identify different types of attacks in general, and the detection rate will be higher for some specific category of attacks. This paper is designed on the idea that each IDS is efficient in detecting a specific type of attack. In proposed Multiple IDS Unit (MIU), there are five IDS units, and each IDS follows a unique algorithm to detect attacks. The feature selection is done with the help of genetic algorithm. The selected features of the input traffic are passed on to the MIU for processing. The decision from each IDS is termed as local decision. The fusion unit inside the MIU processes all the local decisions with the help of majority voting rule and makes the final decision. The proposed system shows a very good improvement in detection rate and reduces the false alarm rate.