Detecting Information Security Threats Using Machine Learning: A Survey of Algorithms and Application Problems

Abstract

This article examines the applicability of machine learning in the context of information security. The main focus is on analyzing the effectiveness of various algorithms and models in strengthening the protection of information systems. This review covers the breadth of machine learning applications to information security problems, presents a wide variety of machine learning methods, and discusses examples of how each of them applies to security-related problems. The article provides examples of how machine learning is used to counter cyber threats, ensure the security of mobile and cloud environments, and automate the threat analysis process. The aim of the work is to systematize relevant research, methods and technologies of machine learning that contribute to improving the level of security and data security in an ever-changing threat landscape.