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

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Author(s): LAHEEB MOHAMMAD IBRAHIM

Journal: Journal of Engineering Science and Technology
ISSN 1823-4690

Volume: 5;
Issue: 4;
Start page: 457;
Date: 2010;
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Keywords: Anomaly | Intrusion detection system | Artificial neural network | Distributed time-delay artificial neural network

ABSTRACT
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%.
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