MACHINE LEARNING METHODS IN INFORMATION SECURITY SYSTEMS
Irina Leonidovna Karpova, A.U. Garkushev · 2024
The rapid spread of the Internet and mobile devices has significantly expanded the boundaries of cyberspace. However, along with the growth of capabilities, it has become more vulnerable to cyber attacks. Existing information security systems are no longer able to cope with new threats. Cybercriminals are constantly improving their methods, easily bypassing traditional defensive lines. Traditional information security systems are ineffective against unknown and polymorphic cyber attacks. The development of machine learning (ML) methods may be the key to solving information security problems in the modern world. Machine learning allows information security systems to be automatically trained based on data, identifying new and previously unknown threats. The article discusses machine learning methods and their application in information security systems, as well as discusses the advantages and disadvantages of using machine learning methods in information security systems.