2025
doi: 10.12720/jait.16.11.1529-1539
Smart Firewall for Phishing Detection Powered by Bio-Inspired Algorithms
Mosleh M. Abualhaj1,*
,
Sumaya N. Al-Khatib2 ,
Ahmad A. Abu-Shareha3 ,
Abdallah Hyassat3 ,
Mohammad Sh. Daoud4
- 1Department of Networks and Cybersecurity, Faculty of Information Technology, Al-Ahliyya Amman University, Amman, Jordan
- 2Department of Computer Science, Faculty of Information Technology, Al-Ahliyya Amman University, Amman, Jordan
- 3Department of Data Science and Artificial Intelligence, Faculty of Information Technology, Al-Ahliyya Amman University, Amman, Jordan
- 4College of Engineering, Al Ain University, Abu Dhabi, United Arab Emirates
- Manuscript receivedJuly 31, 2025
- revisedAugust 12, 2025
- acceptedAugust 21, 2025
- publishedNovember 7, 2025
Abstract
Phishing attacks continue to pose significant risks to digital security by exploiting user vulnerabilities through deceptive methods. This paper presents a smart firewall model for phishing detection that leverages bio-inspired algorithms to enhance threat identification and response. The model utilizes the Whale Optimization Algorithm (WOA) and Dragonfly Algorithm (DA) independently for effective feature selection, thereby reducing data dimensionality while retaining critical phishing indicators. These optimized features are then processed by advanced Machine Learning (ML) classifiers—Extra Trees (ET), Random Forest (RF), and K-Nearest Neighbors (KNN)—to rigorously evaluate detection accuracy. Experimental results on the ISCX-URL2016 dataset demonstrate that the combination of WOA with the ETs classifier achieves a superior detection accuracy of 98.86%, precision of 99.50%, recall of 99.50%, F1-Score of 99.50%, outperforming alternative configurations and recent methods. This result highlights the potential of bio-inspired optimization combined with ML to develop intelligent, adaptive firewalls capable of effectively mitigating phishing threats.
Keywords
- smart firewall
- phishing detection
- bio-inspired algorithms
- feature selection
- machine learning
How to Cite
Mosleh M. Abualhaj, Sumaya N. Al-Khatib, Ahmad A. Abu-Shareha, Abdallah Hyassat, and Mohammad Sh. Daoud, "Smart Firewall for Phishing Detection Powered by Bio-Inspired Algorithms," Journal of Advances in Information Technology, vol. 16, no. 11, pp. 1529-1539, 2025. https://doi.org/10.12720/jait.16.11.1529-1539
Copyright & License
Copyright © 2025 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
