Using feature selection for intrusion detection system

Alazab, Ammar, Hobbs, Michael, Abawajy, Jemal and Alazab, Moutaz 2012, Using feature selection for intrusion detection system, in ISCIT 2012 : Proceedings of the 12th IEEE International Symposium on Communications and Information Technologies, IEEE, [Piscataway, N. J.], pp. 296-301.

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Title Using feature selection for intrusion detection system
Author(s) Alazab, Ammar
Hobbs, Michael
Abawajy, Jemal
Alazab, Moutaz
Conference name International Symposium on Communications and Information Technologies (12th : 2012 : Gold Coast, Qld)
Conference location Gold Coast, Qld
Conference dates 2-5 Oct. 2012
Title of proceedings ISCIT 2012 : Proceedings of the 12th IEEE International Symposium on Communications and Information Technologies
Editor(s) [unknown]
Publication date 2012
Conference series International Symposium on Communications and Information Technologies
Start page 296
End page 301
Total pages 6
Publisher IEEE
Place of publication [Piscataway, N. J.]
Keyword(s) feature selection
intrusion detection
security
Summary A good intrusion system gives an accurate and efficient classification results. This ability is an essential functionality to build an intrusion detection system. In this paper, we focused on using various training functions with feature selection to achieve high accurate results. The data we used in our experiments are NSL-KDD. However, the training and testing time to build the model is very high. To address this, we proposed feature selection based on information gain, which can detect several attack types with high accurate result and low false rate. Moreover, we executed experiments to category each of the five classes (probe, denial of service (DoS), user to super-user (U2R), and remote to local (R2L), normal). Our proposed outperform other state-of-art methods.
ISBN 9781467311571
Language eng
Field of Research 080303 Computer System Security
Socio Economic Objective 970108 Expanding Knowledge in the Information and Computing Sciences
HERDC Research category E1 Full written paper - refereed
Copyright notice ©2012, IEEE
Persistent URL http://hdl.handle.net/10536/DRO/DU:30048268

Document type: Conference Paper
Collection: School of Information Technology
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