Advanced Exploration of Machine Learning in Cybersecurity: A Comprehensive Analysis

In recent years, numerous researchers and professionals have uncovered the susceptibility of wireless communication technologies and systems to a range of cyber threats. These incursions not only jeopardize private enterprises but also pose a significant risk to governmental entities. Across the globe, researchers have proposed various strategies aimed at either preventing or mitigating the damage caused by these cyberattacks. While some of these methods have been adopted, others remain under investigation. This study aims to assess and comprehensively examine the prevailing trends in development, recent breakthroughs, and security challenges within the realm of cybersecurity. The primary constituents of these techniques for detecting cybersecurity risks encompass fraud, intrusion, spam, and virus detection. In this article, we extend the existing body of research on the utilization of machine learning models in cybersecurity and furnish a detailed analysis of machine learning methodologies.