AI-Based Phishing Website Detection Using Machine Learning
Year: 2026
Type: article
Abstract: This research addresses the growing threat of phishing attacks in the digital era by proposing an automated AI-based phishing website detection system. The project focuses on utilizing machine learning to distinguish between phishing and legitimate websites with high precision. Key highlights of this work include: Feature Extraction: The system leverages URL-based and domain-based features for effective classification. Model Evaluation: Three supervised learning models—Logistic Regression, Support Vector Machine (SVM), and Random Forest—were rigorously evaluated. Top Performance: Experimental analysis shows that the Random Forest classifier outperformed others, achieving a peak accuracy of 97.8%. Practical Use: The proposed system is designed for high efficiency and real-time applicability within modern cybersecurity infrastructures.
Author: Md., Taufikuzzaman
Language: English
Topic: Spam and Phishing Detection
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W7129780386
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