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ANALYSIS OF THE USE OF ADAPTIVE MACHINE LEARNING METHODS TO THE TASK OF INTRUSION DETECTION IN A COMPUTER NETWORK

Nesterov Sergey Gennadievich  (postgraduate, Federal State Budgetary Educational Institution of Higher Education «MIREA – Russian Technological University» )

Objective: to study adaptive machine learning methods used to detect intrusions into computer networks in order to increase the efficiency and accuracy of the threat detection system. Methods: to achieve this goal, methods of analysis and generalization of the results of scientific research devoted to the development of adaptive algorithms for detecting anomalies in network traffic were used. Results: as a result of the study, it was shown that the use of adaptive machine learning methods based on incremental learning and the use of artificial neural networks makes it possible to increase the effectiveness of intrusion detection in computer networks. Systems using such methods demonstrate high accuracy and the ability to adapt to changes in the network environment and attack methods. The results of the study confirm the prospects of using adaptive machine learning methods in the field of information security and the need for their further development.

Keywords:analysis, task, adaptive method, network
 

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Citation link:
Nesterov S. G. ANALYSIS OF THE USE OF ADAPTIVE MACHINE LEARNING METHODS TO THE TASK OF INTRUSION DETECTION IN A COMPUTER NETWORK // Современная наука: актуальные проблемы теории и практики. Серия: Естественные и Технические Науки. -2024. -№03. -С. 88-92 DOI 10.37882/2223-2966.2024.03.24
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