Implementation of Machine learning based Network Intrusion Detection System

Please use this identifier to cite or link to this item: https://repository.sustech.edu/handle/123456789/9664

Title:	Implementation of Machine learning based Network Intrusion Detection System
Authors:	Mohammed, Alaa Ahmed Abdallah Basheer, Alnazeer Ali Saw, Mohammed Abdallah Ahmed Haj nasir, Mohammed Shawgy Abdel rahman
Keywords:	Electronics Engineering Machine learning based Network Intrusion Detection
Issue Date:	10-Sep-2014
Publisher:	Sudan University of Science and Technology
Citation:	Mohammed,Alaa Ahmed Abdallah.Implementation of Machine learning based Network Intrusion Detection System/Alaa Ahmed Abdallah Mohammed ...{etal};Abuagla Babiker Mohammed.-Khartuom:Sudan University of Science and Technology, College of Engineering,2014.-55p.: ill ; 28cm.-Bachelors’Search
Abstract:	Recently network attack has been spreaded in computer networks. They can Penetrates through user’s terminal and then cause damage to the system as general. This research aims to find solution for this trouble by implementing intrusion detection system which able to monitor the network traffic and analyse it to extract features, moreover using artificial tool Weka to classify the traffic (anomalous or not). in this research, several classification algorithms have been tested and evaluated to perform the task of detecting the intruders, among them J48 is considered the optimum choice reasonable accuracy 99.6122% with minimum testing time 2.9 sec.
Description:	Bachelors’Search
URI:	http://repository.sustech.edu/handle/123456789/9664
Appears in Collections:	Bachelor of Engineering

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