JSE_V7_N3_RP4 B. Mahalakshmi S. Anandamurugan Journal on Software Engineering 2230–7168 7 3 26 31 Intrusion Detection, NSLKD datasets, Particle Swarm Optimization, AdaBoost Algorithm The network intrusion detection techniques are important to prevent our systems and networks from malicious behaviors. However, traditional network intrusion prevention such as firewalls, user authentication and data encryption have failed to completely protect networks and systems from the increasing the attacks and malwares. Existing system has proposed a new hybrid intrusion detection system by using intelligent dynamic swarm based rough set (IDS-RS) for feature selection and simplified swarm optimization for intrusion data classification. The purpose of this new local search strategy is to get the better solution from the neighborhood of the current solution produced by Simplified Swarm Optimization SSO. Inorder to improve the performance of SSO and Rough Set Theory, Particle Swarm Optimization (PSO) and Enhanced Adaboost is used. It is also used to improve the detection rate and to reduce the false alarm rate. January - March 2013 Copyright © 2013 i-manager publications. All rights reserved. i-manager Publications http://www.imanagerpublications.com/Article.aspx?ArticleId=2172