Genetic programming approach for multi-category pattern classification applied to network intrusions detection
Joint Authors
Source
The International Arab Journal of Information Technology
Issue
Vol. 4, Issue 3 (31 Jul. 2007), pp.237-246, 10 p.
Publisher
Publication Date
2007-07-31
Country of Publication
Jordan
No. of Pages
10
Main Subjects
Information Technology and Computer Science
Topics
Abstract EN
This paper describes a new approach of classification using genetic programming.
The proposed technique consists of genetically coevolving a population of non-linear transformations on the input data to be classified, and map them to a new space with a reduced dimension, in order to get a maximum inter-classes discrimination.
The classification of new samples is then performed on the transformed data, and so become much easier.
Contrary to the existing GP-classification techniques the proposed one use a dynamic repartition of the transformed data in separated intervals, the efficacy of a given intervals repartition is handled by the fitness criterion, with a maximum classes discrimination.
Experiments were first performed using the Fisher’s Iris dataset, and then, the KDD’99 Cup dataset was then used to study the intrusion detection and classification problem.
Obtained results demonstrate that the proposed genetic approach outperform the existing GP-classification methods, and give a very accepted results compared to other existing techniques.
American Psychological Association (APA)
Faraoun, Kamel& Boukelif, Awwad. 2007. Genetic programming approach for multi-category pattern classification applied to network intrusions detection. The International Arab Journal of Information Technology،Vol. 4, no. 3, pp.237-246.
https://search.emarefa.net/detail/BIM-11689
Modern Language Association (MLA)
Faraoun, Kamel& Boukelif, Awwad. Genetic programming approach for multi-category pattern classification applied to network intrusions detection. The International Arab Journal of Information Technology Vol. 4, no. 3 (Jul. 2007), pp.237-246.
https://search.emarefa.net/detail/BIM-11689
American Medical Association (AMA)
Faraoun, Kamel& Boukelif, Awwad. Genetic programming approach for multi-category pattern classification applied to network intrusions detection. The International Arab Journal of Information Technology. 2007. Vol. 4, no. 3, pp.237-246.
https://search.emarefa.net/detail/BIM-11689
Data Type
Journal Articles
Language
English
Notes
includes bibliographical references : p. 245-246
Record ID
BIM-11689