Methodology for detecting anomalies in cyber attack assessment data using Random Forest and Gradient Boosting in machine learning

Methodology for detecting anomalies in cyber attack assessment data using Random Forest and Gradient Boosting in machine learning

Objective. The research aims to detect anomalies in data using machine learning models, in particular random forest and gradient boosting, to analyze network activity and detect cyberattacks. The research topic is relevant as cyber attacks are becoming increasingly complex and sophisticated. Develop...

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Bibliographic Details
Main Authors: A. S. Kechedzhiev, O. L. Tsvetkova, A. I. Dubrovina
Format: Article
Language:Russian
Published: Dagestan State Technical University 2024-10-01
Series:Вестник Дагестанского государственного технического университета: Технические науки
Subjects:
data anomaly
machine learning
random forest algorithm
gradient boosting model
Online Access:https://vestnik.dgtu.ru/jour/article/view/1557
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