Cybersecurity of smart grids: Comparison of machine learning approaches training for anomaly detection

Cybersecurity of smart grids: Comparison of machine learning approaches training for anomaly detection

Objectives. The transformation of modern electric grids into decentralized smart grids presents new challenges in the field of cybersecurity. The purpose of this work is to conduct research and analysis into the effectiveness of different machine-learning methods for identifying anomalies in decentr...

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Bibliographic Details
Main Authors: S. V. Kochergin, S. V. Artemova, A. A. Bakaev, E. S. Mityakov, Zh. G. Vegera, E. A. Maksimova
Format: Article
Language:Russian
Published: MIREA - Russian Technological University 2024-12-01
Series:Российский технологический журнал
Subjects:
smart grids
cybersecurity
machine learning
anomaly detection
isolation forest
cyberattacks
Online Access:https://www.rtj-mirea.ru/jour/article/view/1025
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