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General Information
    • ISSN: 2010-3751 (Print)
    • Frequency: Quarterly
    • DOI: 10.18178/IJFCC
    • Editor-in-Chief: Prof. Mohamed Othman
    • Executive Editor: Ms. Cherry L. Chan
    • Abstracting/ Indexing: Crossref, Electronic Journals LibraryEI (INSPEC, IET), EBSCO, etc.
    • E-mail:  ijfcc@ejournal.net 
Prof. Mohamed Othman
Department of Communication Technology and Network Universiti Putra Malaysia, Malaysia
It is my honor to be the editor-in-chief of IJFCC. The journal publishes good papers in the field of future computer and communication. Hopefully, IJFCC will become a recognized journal among the readers in the filed of future computer and communication.
IJFCC 2015 Vol.4(4): 280-285 ISSN: 2010-3751
DOI: 10.7763/IJFCC.2015.V4.402

A Novel Incremental Instruct Dynamic Intrusion Detection System Using PSO-RBF

M. V. Siva Prasad and Ravi Gottipati
Abstract—This research paper is an elaboration of Incremental Radial Based Function Neural Network model with Particles Swarm Optimization (IRBF-PSO) in Intrusion Detection System. This system is helpful to find the most featured misuse and anomaly detection. RBF network is most popular real-time classifier method. RBF method comprises of mostly analysis and the thorny part is finding the right weights and bias values for dynamic systems. The intrusion detection system has become highly dynamic. Many large or small enterprise systems are still facing with different problems in this area with dynamic form. So the main objective of my work is to employ Particles Swarm Optimization to detect the right weight and bias values for RBF method.
In this method, apart from training with existing data and information for design, there is a need to extend or redesign the existing system to identify different pattern types and modulate the system using PSO with new patterns. After experimentation, this method has improved to identify the difficulty in anomaly detections and reduce the rate of false alarm and fail cases.

Index Terms—Incremental method, intrusion detection system, particles swarm optimization and radial based.

M. V. Siva Prasadis is with Anurag Engineering College, Kodad 508206, India (e-mail: magantisivaprasad@gmail.com).
Ravi Gottipati is with Tripod Technologies, Hyderabad 500082, India (e-mail: softtotime@gmail.com).


Cite: M. V. Siva Prasad and Ravi Gottipati, "A Novel Incremental Instruct Dynamic Intrusion Detection System Using PSO-RBF," International Journal of Future Computer and Communication vol. 4, no. 4, pp. 280-285, 2015.

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