机器学习检测网络攻击和判别电力系统干扰类型

Q4 Engineering
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引用次数: 0

摘要

本研究提出了一种基于机器学习的电力系统攻击检测模型,特别是针对智能电网。通过利用从相量测量设备(pmu)收集的数据和日志,该模型旨在学习系统行为并有效识别潜在的安全边界。该方法涉及数据集预处理、特征选择、模型创建和评估等关键阶段。为了验证我们的方法,我们使用了一个数据集,该数据集由来自不同pmu的15个独立数据集组成,中继snort警报和日志。三种机器学习模型:随机森林、逻辑回归和k近邻模型被建立并使用各种性能指标进行评估。研究结果表明,随机森林模型在电力系统扰动检测中达到了最高的性能,准确率为90.56%,具有辅助运营商决策的潜力
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Machine Learning to Detect Cyber-Attacks and Discriminating the Types of Power System Disturbances
This research proposes a machine learning-based attack detection model for power systems, specifically targeting smart grids. By utilizing data and logs collected from Phasor Measuring Devices (PMUs), the model aims to learn system behaviors and effectively identify potential security boundaries. The proposed approach involves crucial stages including dataset preprocessing, feature selection, model creation, and evaluation. To validate our approach, we used a dataset used, consist of 15 separate datasets obtained from different PMUs, relay snort alarms and logs. Three machine learning models: Random Forest, Logistic Regression, and K-Nearest Neighbour were built and evaluated using various performance metrics. The findings indicate that the Random Forest model achieves the highest performance with an accuracy of 90.56% in detecting power system disturbances and has the potential in assisting operators in decision-making processes
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来源期刊
Journal of Electrical and Electronics Engineering
Journal of Electrical and Electronics Engineering Engineering-Electrical and Electronic Engineering
CiteScore
0.90
自引率
0.00%
发文量
0
审稿时长
16 weeks
期刊介绍: Journal of Electrical and Electronics Engineering is a scientific interdisciplinary, application-oriented publication that offer to the researchers and to the PhD students the possibility to disseminate their novel and original scientific and research contributions in the field of electrical and electronics engineering. The articles are reviewed by professionals and the selection of the papers is based only on the quality of their content and following the next criteria: the papers presents the research results of the authors, the papers / the content of the papers have not been submitted or published elsewhere, the paper must be written in English, as well as the fact that the papers should include in the reference list papers already published in recent years in the Journal of Electrical and Electronics Engineering that present similar research results. The topics and instructions for authors of this journal can be found to the appropiate sections.
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