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

Glubotsky Daniil Timofeevich  (MIREA - Russian Technological University)

Rusakov Alexey Mikhailovich  (senior lecturer MIREA - Russian Technological University )

Koryagin Sergey Viktorovich  (Candidate of Technical Sciences, Associate Professor MIREA - Russian Technological University )

Filatov Vyacheslav Valeryevich  (Associate Professor, Candidate of Technical Sciences, Associate Professor MIREA - Russian Technological University )

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.
 

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Citation link:
Glubotsky D. T., Rusakov A. M., Koryagin S. V., Filatov V. V. DEVELOPMENT OF METHODS AND ALGORITHMS FOR USER SUPPORT IN INFORMATION SECURITY INCIDENTS BASED ON MACHINE LEARNING METHODS // Современная наука: актуальные проблемы теории и практики. Серия: Естественные и Технические Науки. -2023. -№06/2. -С. 44-50 DOI 10.37882/2223-2966.2023.6-2.09
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