ANOMALY NETWORK INTRUSION DETECTION SYSTEM BASED ON DISTRIBUTED TIME-DELAY NEURAL NETWORK (DTDNN)

In this research, a hierarchical off-line anomaly network intrusion detection system based on Distributed Time-Delay Artificial Neural Network is introduced. This research aims to solve a hierarchical multi class problem in which the type of attack (DoS, U2R, R2L and Probe attack) detected by dynami...

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Bibliographic Details
Published in:	Journal of engineering science & technology Vol. 5; no. 4; pp. 457 - 471
Main Author:	LAHEEB MOHAMMAD IBRAHIM
Format:	Journal Article
Language:	English
Published:	Taylor's University 01-12-2010
Subjects:	Anomaly Artificial neural network Distributed time-delay artificial neural network Intrusion detection system
Online Access:	Get full text
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Summary:	In this research, a hierarchical off-line anomaly network intrusion detection system based on Distributed Time-Delay Artificial Neural Network is introduced. This research aims to solve a hierarchical multi class problem in which the type of attack (DoS, U2R, R2L and Probe attack) detected by dynamic neural network. The results indicate that dynamic neural nets (Distributed Time-Delay Artificial Neural Network) can achieve a high detection rate, where the overall accuracy classification rate average is equal to 97.24%.
ISSN:	1823-4690