风电场SCADA系统网络安全风险及机器学习入侵检测方法研究
Research on Wind Farm SCADA Systems Cyber Security Risk and Machine Learning Intrusion Detection Method
钱凯 1康磊 1王庆书1
作者信息
- 1. 华电(云南)新能源发电有限公司集控中心,云南昆明,651000
- 折叠
摘要
随着"双碳"目标的提出,可再生能源的发展和利用进入了高质量跃升发展的新阶段.风能作为一种清洁且丰富的能源形式,具有分布广泛、无污染、可再生等优势,逐渐受到广泛关注.然而随着信息化与工业化深度融合,风电场SCADA(Supervisory Control And Data Acquisition,数据采集与监视控制系统)系统的信息化程度不断提高,网络安全问题日益突出.为了应对这些问题,机器学习以其强大的数据处理和模式识别能力,成为一种有效的入侵检测方法,可有效检测异常行为,预防潜在网络安全威胁.其中支持向量机(SVM)、卷积神经网络(CNN)、循环神经网络(RNN)以及单类支持向量机(OCSVM)等模型可应用于风电场SCADA系统入侵检测,提高风电场SCADA系统的网络安全性,保障系统稳定运行.本文首先概述了机器学习算法,随后探讨了风电场SCADA系统面临的网络安全风险,并介绍了机器学习在入侵检测方面的应用价值及适用场景,以期为机器学习在风电场SCADA系统入侵检测的应用研究方向提供参考借鉴.
Abstract
With the proposal of the"Double Carbon"goal,the development and utilization of renewable energy has entered a new stage of high-quality development.As a clean and abundant form of energy,wind energy is widely distributed,pollution-free,renewable,and gradually attracted wide attention.However,with the deep integration of informatization and industrialization,the degree of informatization of wind farm SCADA(Supervisory Control And Data Acquisition)systems continues to increase,and cyber security issues are becoming increasingly prominent.In response to these issues,machine learning,with its powerful data processing and pattern recognition capabilities,has become an effective intrusion detection method,which can effectively detect abnormal behavior and preventing potential cybersecurity threats.Models such as Support Vector Machine(SVM),Convolutional Neural Network(CNN),Recurrent Neural Network(RNN),and One-Class Support Vector Machine(OCSVM)can be applied to intrusion detection in wind farm SCADA systems,enhancing the cybersecurity of wind farm SCADA systems and ensuring stable operation of the system.This paper first outlines machine learning algorithms,then discusses the cyber security risks faced by wind farm SCADA systems,and introduces the application value and applicable scenarios of machine learning in intrusion detection,in order to provide reference for the application research direction of machine learning in intrusion detection of wind farm SCADA systems.
关键词
机器学习/风电场/数据采集与监控系统/入侵检测/网络安全Key words
Machine Learning/Wind Farms/SCADA/Intrusion Detection/Cyber Security引用本文复制引用
出版年
2024
NETL
NSTL
万方数据