DEVELOPMENT OF METHODS AND ALGORITHMS FOR USER SUPPORT IN INFORMATION SECURITY INCIDENTS BASED ON MACHINE LEARNING METHODS

Glubotsky Daniil Timofeevich, Rusakov Alexey Mikhailovich, Koryagin Sergey Viktorovich, Filatov Vyacheslav Valeryevich

This article discusses the development of methods and algorithms for user support in information security incidents based on machine learning methods. The article describes the advantages of using machine learning for analyzing large amounts of data related to information security incidents, and proposes methods for solving the classification and risk prediction tasks based on logistic regression, decision trees, and neural networks. The analysis carried out showed that the use of neural networks allows achieving the best results compared to other methods. In conclusion, it is noted that the developed methods and algorithms can be used for effective user support in information security incidents and increasing the overall security of information systems.

Keywords:information security, machine learning, user support, information security incidents.