Назва: Development of network traffic monitoring system elements using Deep Learning
| custom.quartile | Scopus (Q4) | |
| dc.contributor.author | Melnyk, Vasyl | |
| dc.contributor.author | Bahniuk, Nataliia | |
| dc.contributor.author | Bortnyk, Kateryna | |
| dc.contributor.author | Kondius, Inna | |
| dc.contributor.author | Zubovetska, Nataliia | |
| dc.contributor.author | Kondius, Kostiantyn | |
| dc.date.accessioned | 2026-06-07T19:36:53Z | |
| dc.date.issued | 2024 | |
| dc.description.abstract | In 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.citation | Melnyk, 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.doi | 10.1109/DESSERT65323.2024.11122254 | |
| dc.identifier.uri | https://repository.lntu.edu.ua/handle/123456789/3557 | |
| dc.language.iso | en | |
| dc.publisher | Piscataway, NJ: IEEE | |
| dc.subject | Deep Learning | |
| dc.subject | Monitoring | |
| dc.subject | Software Tool | |
| dc.subject | Network Traffic | |
| dc.title | Development of network traffic monitoring system elements using Deep Learning | |
| dc.type | Article | |
| dspace.entity.type | ScientificArticle |
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