Anomaly traffic detection based on PCA and SFAM
Joint Authors
Somwang, Preecha
Lilakiatsakun, Woraphon
Source
The International Arab Journal of Information Technology
Issue
Vol. 12, Issue 3 (31 May. 2015), pp.253-260, 8 p.
Publisher
Publication Date
2015-05-31
Country of Publication
Jordan
No. of Pages
8
Main Subjects
Topics
Abstract EN
Intrusion Detection System (IDS) has been an important tool for network security.
However, existing IDSs that have been proposed do not perform well for anomaly traffics especially Remote to Local (R2L) attack which is one of the most concerns.
We thus propose a new efficient technique to improve IDS performance focusing mainly on R2L attacks.
The Principal Component Analysis (PCA) and Simplified Fuzzy Adaptive resonance theory Map (SFAM) are used to work collaboratively to perform feature selection.
The results of our experiment based on KDD Cup’99 dataset show that this hybrid method improves classification performance of R2L attack significantly comparing to other techniques while classification of the other types of attacks are still well performing.
American Psychological Association (APA)
Somwang, Preecha& Lilakiatsakun, Woraphon. 2015. Anomaly traffic detection based on PCA and SFAM. The International Arab Journal of Information Technology،Vol. 12, no. 3, pp.253-260.
https://search.emarefa.net/detail/BIM-581944
Modern Language Association (MLA)
Somwang, Preecha& Lilakiatsakun, Woraphon. Anomaly traffic detection based on PCA and SFAM. The International Arab Journal of Information Technology Vol. 12, no. 3 (May. 2015), pp.253-260.
https://search.emarefa.net/detail/BIM-581944
American Medical Association (AMA)
Somwang, Preecha& Lilakiatsakun, Woraphon. Anomaly traffic detection based on PCA and SFAM. The International Arab Journal of Information Technology. 2015. Vol. 12, no. 3, pp.253-260.
https://search.emarefa.net/detail/BIM-581944
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references : p. 258-260
Record ID
BIM-581944