Zamonaviy dunyoda amaliy fanlar 5-jild 12-son (2026) · 11–18-betlar

MACHINE LEARNING TECHNIQUES FOR NETWORK ANOMALY DETECTION IN ENTERPRISE NETWORKS

Kushmanova, Mahbuba, G‘ulomjonov, Xurshidbek

DOI: 10.5281/zenodo.20588952 · Manbada o'qish → · PDF (manba serverida)

Annotatsiya

Today, the growing volume of data in enterprise networks and the increasing sophistication of cyberattacks make network security a critical challenge. This article explores the potential of machine learning techniques for detecting anomalies in enterprise networks. The limitations of traditional security solutions are discussed, and the advantages of artificial intelligence technologies in analyzing network traffic and identifying suspicious activities are highlighted. In addition, the paper examines the role of machine learning algorithms in the early detection of cyber threats and their contribution to improving overall network security.

machine learning, network anomalies, cybersecurity, artificial intelligence, network traffic, attack detection, enterprise networks, data analysis, anomaly detection, network security.

Metadata manbasi: jurnal OAI-PMH arxivi · Sindex to'liq matnni saqlamaydi, manbaga havola beradi.