A Survey on the Landscape of Machine Learning Solutions for Detecting Phishing Attacks
Shijon Das, Mohamed I. Ibrahem, Mostafa M. Fouda · 2024
Despite the advancements in cybersecurity, phishing attacks continue to pose significant threats to organizations and individuals worldwide. With the advent of time, phishing techniques have become more robust and thus demand more enhanced solutions than the existing ones. This survey paper explores how machine learning (ML) techniques are applied for detecting phishing attacks, offering a comprehensive overview of the challenges faced and the advancements made in the field. The paper discusses the fundamentals of phishing attacks and how ML can be applied to detect those attacks. The paper also discusses the applications of deep learning models and anomaly detection techniques which offer precise results for detecting modern phishing strategies. Finally, this survey addresses the challenges faced by current detection systems and suggests potential areas for future research. The goal of this survey is to provide a comprehensive overview that not only discusses the existing machine learning techniques but at the same time inspires innovation in this domain.