FARIMA Model Based Analysis of Communication Traffic Anomaly in Smart Substation

被引：0
|
作者：
Hao W. [1 ,2 ]
Yang Q. [1 ,2 ]
Li W. [3 ]
机构：
[1] College of Electrical Engineering, Zhejiang University, Hangzhou
[2] Zhejiang Laboratory, Hangzhou
[3] School of Information Technologies, The University of Sydney, Sydney
来源：
Dianli Xitong Zidonghua/Automation of Electric Power Systems | 2019年 / 43卷 / 01期
基金：
中国国家自然科学基金;
关键词：
Communication traffic; Fractional autoregressive integrated moving average (FARIMA) model; IEC; 61850; Regression model; Smart substation;
D O I：
10.7500/AEPS20180705012
中图分类号：
学科分类号：
摘要：
With the rapid development of power transmission and transformation equipment automation and smart substation construction, the hidden danger of grid information security is increasingly prominent. Accurate and reliable traffic modeling and anomaly detection method of substation communication network (SCN) have become very important to prevent network security problems and identify cyber attacks. Based on the analysis of behavior characteristics of network traffic on the control layer of substation station, this paper proposes the fractional autoregressive integrated moving average (FARIMA) model to construct the threshold model for network traffic. Aiming at the typical cyber-attack mode and traffic anomaly characteristics of substation, the traffic data on the control layer of an actual substation station is analyzed based on the operation state assessment algorithm. And the probability of typical network anomaly is calculated. Finally, the safety situation evaluation of the substation is realized under the cyber attacks. © 2019 Automation of Electric Power Systems Press.
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页码：158 / 167
页数：9
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