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Dalia N. Abdul-Wadood
University Of Bagdad
Computer Science & IT Electrical & Electronics Engineering

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Botnet detection using ensemble classifiers of network flow Zahraa M. Algelal; Eman Abdulaziz Ghani Aldhaher; Dalia N. Abdul-Wadood; Radhwan Hussein Abdulzhraa Al-Sagheer
International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 3: June 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (532.334 KB) | DOI: 10.11591/ijece.v10i3.pp2543-2550

Abstract

Recently, Botnets have become a common tool for implementing and transferring various malicious codes over the Internet. These codes can be used to execute many malicious activities including DDOS attack, send spam, click fraud, and steal data. Therefore, it is necessary to use Modern technologies to reduce this phenomenon and avoid them in advance in order to differentiate the Botnets traffic from normal network traffic. In this work, ensemble classifier algorithms to identify such damaging botnet traffic. We experimented with different ensemble algorithms to compare and analyze their ability to classify the botnet traffic from the normal traffic by selecting distinguishing features of the network traffic. Botnet Detection offers a reliable and cheap style for ensuring transferring integrity and warning the risks before its occurrence.
Co-Authors Eman Abdulaziz Ghani Aldhaher Radhwan Hussein Abdulzhraa Al-Sagheer Zahraa M. Algelal