Machine Learning Based on the Client Side Protection Versus Online Phishing Threats

The use of machine learning algorithms for client-side defense against online phishing attacks is examined in this study. We examine several machine learning algorithms and how well they detect phishing attempts, emphasizing the benefits of putting these fixes straight on client devices. Our findings show that while maintaining user privacy, client-side machine learning (ML)-based security provides substantial gains in real-time threat detection. We compare several ML techniques through experimental findings and explain the implications for improving online security.