智能变电站过程层网络异常流量检测
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引用本文:刘 见 ,赵震宇,裴茂林,杨爱超,单 鹏,刘 明.智能变电站过程层网络异常流量检测[J].计算技术与自动化,2021,(3):184-188
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刘 见 ,赵震宇,裴茂林,杨爱超,单 鹏,刘 明 (国网江西省电力有限公司 电力科学研究院江西 南昌 330096) 
中文摘要:为了避免智能变电站过程层网络通信出现异常变动的现象,需要准确检测智能变电站过程层网络异常流量,为此提出新型的检测方法。设计了基于网络演算的变电站通信网络流量计算模型,将根节点全部设成信源,通过流量路由实现周围输入与输出端口的联系,获取智能变电站过程层网络中全部设备端口输入与输出流量。还应用优化支持向量模型进行异常流量检测,将网络异常流量与正常流量分类,实现智能变电站过程层网络异常流量检测。实验结表明:在检测,网络流量特征提取、异常流量检测效果均符合应用需求。
中文关键词:智能变电站  过程层网络  异常流量检测  网络演算  支持向量模型
 
Abnormal Flow Detection of Process Layer Network in Intelligent Substation
Abstract:In order to avoid abnormal changes in the network communication at the process level of the smart substation, it is necessary to accurately detect the abnormal traffic at the process level network of the smart substation. To this end, a new detection method is proposed. In this study, a substation communication network flow calculation model based on network calculus is designed, all root nodes are set as sources, and the surrounding input and output ports are connected through flow routing to obtain the input and output flow of all equipment ports in the process layer network of the intelligent substation . This study also uses the optimized support vector model to detect abnormal traffic, classify network abnormal traffic from normal traffic, and implement network abnormal traffic detection at the process level of intelligent substations. The experimental results show that: in this study, the network traffic feature extraction and abnormal traffic detection effects all meet the application requirements.
keywords:intelligent substation  process layer network  abnormal flow detection  network calculus  support vector model
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