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Development of network traffic monitoring system elements using Deep Learning

custom.quartileScopus (Q4)
dc.contributor.authorMelnyk, Vasyl
dc.contributor.authorBahniuk, Nataliia
dc.contributor.authorBortnyk, Kateryna
dc.contributor.authorKondius, Inna
dc.contributor.authorZubovetska, Nataliia
dc.contributor.authorKondius, Kostiantyn
dc.date.accessioned2026-06-07T19:36:53Z
dc.date.issued2024
dc.description.abstractIn this article we develop a network traffic monitoring system elements using deep learning that demonstrates the high effectiveness of deep learning in detecting and analyzing network traffic, which contributes to ensuring the security and stability of corporate networks. In this context we develop algorithms for detecting and countering potential threats in network traffic, providing deeper analysis and effective response to cyber threats
dc.identifier.citationMelnyk, V., Bahniuk, N., Bortnyk, K., Kondius, I., Zubovetska, N., & Kondius, K. Development of Network Traffic Monitoring System Elements Using Deep Learning. Dependable Systems, Services and Technologies: 14th International Conference. (Athens, Greece, October 11–13, 2024.). Piscataway, NJ: IEEE, 2024. P. 1–7.
dc.identifier.doi10.1109/DESSERT65323.2024.11122254
dc.identifier.urihttps://repository.lntu.edu.ua/handle/123456789/3557
dc.language.isoen
dc.publisherPiscataway, NJ: IEEE
dc.subjectDeep Learning
dc.subjectMonitoring
dc.subjectSoftware Tool
dc.subjectNetwork Traffic
dc.titleDevelopment of network traffic monitoring system elements using Deep Learning
dc.typeArticle
dspace.entity.typeScientificArticle

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