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Detection Method of DC Microgrid Network Attack Based on Two-level and Multi-segment Model
Wireless Personal Communications ( IF 2.2 ) Pub Date : 2021-07-01 , DOI: 10.1007/s11277-021-08711-w
Liren Zou

Because the current method of attack detection of current flow microgrid is slow, it leads to the increase of detection time. Therefore, a two-stage segmentation model based attack detection method for DC microgrid network is proposed. The structure of DC microgrid is analyzed, the model of DC microgrid network is constructed, and the sparse region of the micro grid network is divided. According to the results of regional division, a two-level and multi-segment model is constructed, which is composed of the above-level central neural network and the lower level is edge end neural network. The parallel computing structure of the model is set up to get the attack detection results of DC microgrid network. The experimental results show that the method has high recall and precision, low error detection rate and short detection time, which can realize the rapid and accurate detection of network attacks.



中文翻译:

基于两级多段模型的直流微电网网络攻击检测方法

由于目前的电流微电网攻击检测方法较慢,导致检测时间增加。为此,提出了一种基于两阶段分割模型的直流微电网攻击检测方法。分析了直流微网的结构,构建了直流微网模型,划分了微网的稀疏区域。根据区域划分的结果,构建两级多段模型,由上级中央神经网络和下级边缘端神经网络组成。建立模型的并行计算结构,得到直流微电网网络攻击检测结果。实验结果表明,该方法召回率和准确率高,错误检测率低,检测时间短,

更新日期:2021-07-01
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