“Intercepting the Invisible: Monitoring and Analyzing Suspicious Web Threat Interactions”: A Review

Abstract

Cybersecurity threats are evolving rapidly, necessitating advanced methods for detecting and mitigating malicious online activities. "Intercepting the Invisible: Monitoring and Analyzing Suspicious Web Threat Interactions" presents a comprehensive study on monitoring web-based threats using machine learning models. This review critically evaluates the article’s contributions, methodologies, and findings, identifying strengths and limitations. While the study offers valuable insights into cybersecurity threat detection, areas for improvement include dataset diversity, real-time implementation, and scalability. This review also explores potential future research directions to enhance the effectiveness of web threat analysis