An Intrusion Detection System Based on Hybrid of Artificial Neural Network (ANN) and Magnetic Optimization Algorithm (MOA)

Authors

  • Siti Norwahidayah Wahab Faculty of Computer, Media and Technology Management, University College TATI
  • Noor Suhana Sulaiman Faculty of Computer, Media and Technology Management, University College TATI
  • Noraniah Abdul Aziz Faculty of Computer, Media and Technology Management, University College TATI
  • Nur Liyana Zakaria Faculty of Computer, Media and Technology Management, University College TATI
  • Ainal Amirah Abd Aziz Faculty of Computer, Media and Technology Management, University College TATI

Keywords:

Artificial Neural Network, Magnetic Optimization Algorithm, Intrusion Detection System, KDD Cup 99, Classification

Abstract

Intrusion Detection System is a type of security application that protects computer and network systems. A variety of techniques have been proposed to increase IDS accuracy. This research study focuses on improving an IDS detection performance by combining an Artificial Neural Network (ANN) with a Magnetic Optimization Algorithm (MOA), with the goal of increasing the classification rate and achieving high detection accuracy in IDS. The suggested ANNMOA result demonstrated that it is possible to improve IDS accuracy by up to 98.5 percent.

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Published

22-06-2022

How to Cite

Wahab, S. N., Sulaiman, N. S., Abdul Aziz, N., Zakaria, N. L., & Abd Aziz, A. A. (2022). An Intrusion Detection System Based on Hybrid of Artificial Neural Network (ANN) and Magnetic Optimization Algorithm (MOA). International Journal of Integrated Engineering, 14(3), 150–156. Retrieved from https://publisher.uthm.edu.my/ojs/index.php/ijie/article/view/10723