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PhishNet 1.0: optuna-optimized stacking ensemble with Boruta-based feature selection for phishing URL detection

Abstract The objective of this research is to enhance phishing detection through ensemble learning integrated with well-structured metaheuristic algorithms. Various classifiers, including Logistic Regression, Nearest Neighbors, Support Vector Machine, Decision Tree, Naïve Bayes, and Gradient Boostin...

Celý popis

Uloženo v:
Hlavní autoři: Achin Jain, Shakir Khan, Kashish Koli, Harsh Taneja, Arvind Panwar, Thamer Alshammari, Essam Mohamed Obaid, Seid Mehammed Abdu
Médium: Artigo
Jazyk:Inglês
Vydáno: Nature Portfolio 2025-12-01
Edice:Scientific Reports
Témata:
Phishing detection
Boruta
Machine learning
Ensemble learning
Stacking
Optimization
On-line přístup:https://doi.org/10.1038/s41598-025-31447-7
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