Enhancing Intrusion Detection System Performance Using a Hybrid of Harris Hawks and Whale Optimization Algorithms

Authors

  • Mosleh M. Abualhaj Department of Networks and Cybersecurity, Faculty of Information Technology, Al-Ahliyya Amman University, Amman, Jordan
  • Sumaya N. Al-Khatib Department of Computer Science, Faculty of Information Technology, Al-Ahliyya Amman University, Amman, Jordan
  • Mahran Al Zyoud Department of Networks and Cybersecurity, Faculty of Information Technology, Al-Ahliyya Amman University, Amman, Jordan
  • Iyas Qaddara Department of Computer Science, Faculty of Information Technology, Al-Ahliyya Amman University, Amman, Jordan
  • Mohammed Anbar Cybersecurity Research Centre (CYRES), Universiti Sains Malaysia (USM), Penang, Malaysia
Volume: 15 | Issue: 4 | Pages: 24354-24361 | August 2025 | https://doi.org/10.48084/etasr.10919

Received: 11 March 2025 | Revised: 5 April 2025 and 20 April 2025 | Accepted: 23 April 2025 | Online: 2 August 2025


Corresponding author: Mosleh M. Abualhaj

Abstract

Intrusion Detection and Prevention Systems (IDPSs) play a crucial role in safeguarding online connections against unauthorized access and malicious activities. To enable efficient and effective detection and mitigation, IDPSs must continuously improve their performance due to the constantly developing nature of cyber threats. However, an IDPS is more difficult to use and less reliable when it deals with huge amounts of data. This study aimed to improve the performance of IDPSs by employing optimization algorithms to reduce the data size. Particularly, the Harris Hawks Optimization (HHO) and Whale Optimization Algorithm (WOA) were combined for feature selection. The experimental results showed that the performance of the proposed IDPS was greatly improved by combining the HHO and WOA algorithms. Combining a Random Forest classifier with the suggested HHO/WOA feature selection method achieved very high results in accuracy (99.17%), recall (98.76%), precision (98.76%), and F1-score (98.43%).

Keywords:

feature selection, Harris hawks optimization algorithm, intrusion detection, machine learning, whale optimization algorithm

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[1]
M. M. Abualhaj, S. N. Al-Khatib, M. Al Zyoud, I. Qaddara, and M. Anbar, “Enhancing Intrusion Detection System Performance Using a Hybrid of Harris Hawks and Whale Optimization Algorithms”, Eng. Technol. Appl. Sci. Res., vol. 15, no. 4, pp. 24354–24361, Aug. 2025.

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Copyright (c) 2025 Mosleh M. Abualhaj, Sumaya N. Al-Khatib, Mahran Al Zyoud, Iyas Qaddara, Mohammed Anbar

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