Statistical and machine learning approaches for detecting anomalies in large-volume network traffic

Raxmonov, Ozodbek

Al-Farg'oniy avlodlari · 2025-yil

Annotatsiya

Detecting anomalies in large-scale network traffic is one of the pressing issues in modern information security. The volume of traffic generated as a result of the expansion of Internet services, cloud computing, the development of IoT and 5G networks is increasing dramatically, and this process reduces the effectiveness of traditional security mechanisms. This article studies and compares statistical methods and machine learning approaches to detect anomalous behavior in the network. The advantages of statistical approaches, analysis of variance and time series models, are explained by their performance and efficiency in real-time monitoring, but their accuracy is limited in large-scale data.

Maqola ma’lumotlari
MualliflarRaxmonov, Ozodbek
JurnalAl-Farg'oniy avlodlari
NashriyotТАТУ Фарғона филиали
ISSN2181-4252
Nashr sanasi2025-10-09
Son3
Betlar194-201
TilIngliz
Ilmiy sohaTexnika
Indeksga qo‘shilgan2026-08-26

Maqolaning asl sahifasi

Kalit so‘zlar

Network traffic analysis, anomaly detection, big data, statistical approaches, supervised learning, unsupervised learning, hybrid model, IoT security, cloud computing, 5G networks, real-time monitoring, post-quantum cryptography, autoencoder

Ilmiy soha

Texnika

Iqtibos keltirish

APARaxmonov, Ozodbek (2025). Statistical and machine learning approaches for detecting anomalies in large-volume network traffic. Al-Farg'oniy avlodlari, (3), 194-201. https://al-fargoniy.uz/index.php/journal/article/view/916
GOST (OAK)Raxmonov, Ozodbek Statistical and machine learning approaches for detecting anomalies in large-volume network traffic // Al-Farg'oniy avlodlari. – 2025. – № 3. – P. 194-201.
MLARaxmonov, Ozodbek. “Statistical and machine learning approaches for detecting anomalies in large-volume network traffic.” Al-Farg'oniy avlodlari, (3), 194-201, 2025. https://al-fargoniy.uz/index.php/journal/article/view/916
ChicagoRaxmonov, Ozodbek. “Statistical and machine learning approaches for detecting anomalies in large-volume network traffic.” Al-Farg'oniy avlodlari, (3), 194-201 (2025). https://al-fargoniy.uz/index.php/journal/article/view/916
HarvardRaxmonov, Ozodbek (2025) ‘Statistical and machine learning approaches for detecting anomalies in large-volume network traffic’, Al-Farg'oniy avlodlari, (3), 194-201. https://al-fargoniy.uz/index.php/journal/article/view/916
BibTeX
@article{raxmonovozodbek2025,
  title = {Statistical and machine learning approaches for detecting anomalies in large-volume network traffic},
  author = {Raxmonov, Ozodbek},
  journal = {Al-Farg'oniy avlodlari},
  year = {2025},
  number = {3},
  pages = {194-201},
  url = {https://al-fargoniy.uz/index.php/journal/article/view/916}
}

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