Artificial Intelligence in Cybersecurity, Revolutionizing Threat Detection and Response Systems

Abstract

This article examines how machine learning (ML) will shape the cybersecurity landscape between 2020 and 2023. The article examines the role of ML in enhancing threat detection capabilities and vulnerabilities to attacks, as well as the increasing material impact of AI-driven cyber scenarios. It focuses on the risks and detection accuracy of research and neural network systems. It also examines the assessment of problem-solving strategies and the balance that combines ML with human expertise. The analysis highlights the importance of leveraging ML capabilities and proactive measures to address their vulnerabilities and achieve a safer digital environment.