INTELLIGENT MULTI-MODEL FRAMEWORK FOR PHISHING DETECTION USING MACHINE LEARNING

Author(s)	Dr. LEVINA TUKARAM, Mr. AMAN SHAIK, Mr. NITESH JHA, Mr. BIBEK PANGENI, Mr. FAHIM AHMAD Mohamed
Country	India
Abstract	Phishing attacks have become so alarming threats in cyber world examination research in recent years. It becomes more sophisticated and dangerous for individual and organizational use. Existing fraudulent activity identification methodologies, like blacklist-based approaches, do not work effectively anymore for the new fraud cases that have emerged in recent times. It has indicated that researchers are turning to ML methods in seeking comprehensively automated identification methods for fraudulent activity websites, malicious e-mails, and harmful files. This literature review encapsulates important contributions on fraudulent activity identification by focusing on different methodologies, feature extraction implementations, and ML models to enhance identification accuracy.
Keywords	Phishing Detection, AI, Machine Learning, Cybersecurity, web address Analysis, Email Security, File Detection, Multi-Model Approach
Field	Computer > Artificial Intelligence / Simulation / Virtual Reality
Published In	Volume 7, Issue 3, May-June 2025
Published On	2025-05-11
DOI	https://doi.org/10.36948/ijfmr.2025.v07i03.44437
Short DOI	https://doi.org/g9kvbp

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International Journal For Multidisciplinary Research