Machine Learning for HTTP Botnet Detection Using Classifier Algorithms

Authors

  • Rudy Fadhlee Mohd Dollah Information Security, Digital Forensic, and Computer Networking (INSFORNET), Faculty of Information Technology and Communication, Universiti Teknikal Malaysia Melaka, Ayer Keroh, Melaka, Malaysia
  • Faizal M. A. Information Security, Digital Forensic, and Computer Networking (INSFORNET), Faculty of Information Technology and Communication, Universiti Teknikal Malaysia Melaka, Ayer Keroh, Melaka, Malaysia
  • Fahmi Arif Department of Industrial Engineering, Institut Teknologi Nasional (Itenas) Bandung. Indonesia
  • Mohd Zaki Mas’ud Information Security, Digital Forensic, and Computer Networking (INSFORNET), Faculty of Information Technology and Communication, Universiti Teknikal Malaysia Melaka, Ayer Keroh, Melaka, Malaysia
  • Lee Kher Xin Information Security, Digital Forensic, and Computer Networking (INSFORNET), Faculty of Information Technology and Communication, Universiti Teknikal Malaysia Melaka, Ayer Keroh, Melaka, Malaysia

Keywords:

Botnet Detection, Classification, Classifier, HTTP Botnet, Machine Learning, Malware,

Abstract

Recently, HTTP based Botnet threat has become a serious problem for computer security experts as bots can infect victim’s computer quick and stealthily. By using HTTP protocol, Bots are able to hide their communication flow within normal HTTP communications. In addition, since HTTP protocol is widely used by internet application, it is not easy to block this service as a precautionary approach. Thus, it is needed for expert finding ways to detect the HTTP Botnet in network traffic effectively. In this paper, we propose to implement machine learning classifiers, to detect HTTP Botnets. Network traffic dataset used in this research is extracted based on TCP packet feature. We also able to find the best machine learning classifier in our experiment. The proposed method is able to classify HTTP Botnet in network traffic using the best classifier in the experiment with an average accuracy of 92.93%.

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Published

2018-02-12

How to Cite

Mohd Dollah, R. F., M. A., F., Arif, F., Mas’ud, M. Z., & Xin, L. K. (2018). Machine Learning for HTTP Botnet Detection Using Classifier Algorithms. Journal of Telecommunication, Electronic and Computer Engineering (JTEC), 10(1-7), 27–30. Retrieved from https://jtec.utem.edu.my/jtec/article/view/3591