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All Journal International Journal of Electrical and Computer Engineering
Tahboush, Muhannad
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Computer Science & IT Electrical & Electronics Engineering

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Phishing detection using grey wolf and particle swarm optimizer Hamdan, Adel; Tahboush, Muhannad; Adawy, Mohammad; Alwada’n, Tariq; Ghwanmeh, Sameh; Husni, Moath
International Journal of Electrical and Computer Engineering (IJECE) Vol 14, No 5: October 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v14i5.pp5961-5969

Abstract

Phishing could be considered a worldwide problem; undoubtedly, the number of illegal websites has increased quickly. Besides that, phishing is a security attack that has several purposes, such as personal information, credit card numbers, and other information. Phishing websites look like legitimate ones, which makes it difficult to differentiate between them. There are several techniques and methods for phishing detection. The authors present two machine-learning algorithms for phishing detection. Besides that, the algorithms employed are XGBoost and random forest. Also, this study uses particle swarm optimization (PSO) and grey wolf optimizer (GWO), which are considered metaheuristic algorithms. This research used the Mendeley dataset. Precision, recall, and accuracy are used as the evaluation criteria. Experiments are done with all features (111) and with features selected by PSO and GWO. Finally, experiments are done with the most common features selected by both PSO and GWO (PSO ∩ GWO). The result demonstrates that system performance is highly acceptable, with an F-measure of 91.4%.
Co-Authors Adawy, Mohammad Alwada’n, Tariq Ghwanmeh, Sameh Hamdan, Adel Husni, Moath