i-manager Publications

Genetic Algorithm's Fitness Value and False Positive in Network Intrusion Detection System

Jeya S*

* Assistant Professor & Head, Department of M. C. A., PET Engineering College, Tirunelveli District, Tamil Nadu.

Periodicity:October - December'2008
DOI : https://doi.org/10.26634/jse.3.2.244

Abstract

Network Intrusion detection systems aim is to detect attacks against computer systems and networks. This paper focuses on the development of Genetic Algorithm in Intrusion Detection System (GAIDS). Genetic Algorithms can provide appropriate heuristic search methods. However, balancing the need to detect all possible attacks found in network with the need to avoid false positives is a challenge, given the scalar fitness values required by Genetic Algorithms. This study discusses a fitness function independent of variable parameters to overcome this problem. This fitness function allows the IDS to significantly reduce both its false positive and false negative rate.

Keywords

Chromosome, Network sniffers, Niching technique, Crossover and Mutation

How to Cite this Article?

Jeya S (2008). Genetic Algorithm's Fitness Value and False Positive in Network Intrusion Detection System. i-manager’s Journal on Software Engineering, 3(2),14-19. https://doi.org/10.26634/jse.3.2.244

References

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Genetic Algorithm's Fitness Value and False Positive in Network Intrusion Detection System

Abstract

Keywords

How to Cite this Article?

References

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