Design of a Network Intrusion Detection System Using Complex Deep Neuronal Networks

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Mohammed Abdulhammed Al-Shabi


Recent years have witnessed a tremendous development in various scientific and industrial fields. As a result, different types of networks are widely introduced which are vulnerable to intrusion. In view of the same, numerous studies have been devoted to detecting all types of intrusion and protect the networks from these penetrations. In this paper, a novel network intrusion detection system has been designed to detect cyber-attacks using complex deep neuronal networks. The developed system is trained and tested on the standard dataset KDDCUP99 via pycharm program. Relevant to existing intrusion detection methods with similar deep neuronal networks and traditional machine learning algorithms, the proposed detection system achieves better results in terms of detection accuracy.

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How to Cite
Al-Shabi, M. A. (2022). Design of a Network Intrusion Detection System Using Complex Deep Neuronal Networks. International Journal of Communication Networks and Information Security (IJCNIS), 13(3). (Original work published December 25, 2021)
Research Articles
Author Biography

Mohammed Abdulhammed Al-Shabi, Department of Management Information System, College of Business Administration, Taibah University, Saudi Arabia

Mohammed Al-Shabi received his bachelor’s degree (B.Sc. Computer Science) from Technology University at Iraq (1997), Postgraduate Master (M. Sc. Computer Science from Putra Malaysia University at 2002), and Ph.D. (Computer Science) from Putra Malaysia University, Malaysia (2006). He is currently an associate professor in the Department of Management Information System, College of Business Administration at Taibah University, Kingdom of Saudi Arabia. Prior to joining Taibah University, he worked in the Faculty of a computer at Qassim University, Saudi Arabia. His research interests include wireless security, cryptography, UML, Stenography Multistage interconnection network, Vehicular Ad-hoc Network-Cloud, Smart and Intelligent computing and Apply Mathematically.


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