Enhancing Phishing Detection using Machine Learning Algorithms

The current article introduces the application of machine learning algorithms to aid phishing, i.e., the application of these algorithms to prepare well-fitting, realistic phishing attacks. Due to the nature of ML in having attributes, including natural language comprehension and pattern recognition ability, phishing attacks have the potential to evade the current traditional security tactic and execute real-time. As per the paper, the supervised learning is being trained for phishing email crafting and the unsupervised learning training for phishing victim behavioral pattern exploitation, illustrating how ML can be effectively utilized to automate and escalate phishing attacks. The findings showcase the need for adaptive ML-based security solutions to detect and counter such emerging threats.