摘要
为了降低智能电表应用中的误报率与计算成本,提出一种基于时间故障传播图支持向量机的计量基础设施攻击识别方法。建立和训练支持向量机模型,用于检测智能电表中的可疑行为;使用时间故障传播图技术生成攻击路径,从而识别攻击事件,并计算检测到的异常事件与预定义网络攻击之间的相似性。在AMI测试平台上进行仿真实验,验证了提出方法的有效性。
In order to reduce the false alarm rate and calculation cost in the application of smart meter,a measurement infrastructure attack identification method based on time fault propagation graph support vector machine is proposed.The support vector machine was established and trained to detect suspicious behavior in smart meter.The attack path was generated by using the time fault propagation graph technology to identify the attack events.The proposed pattern recognition algorithm was used to calculate the similarity between the detected abnormal events and predefined network attacks.The simulation results on AMI test platform show the effectiveness of the proposed method.
作者
戴玉艳
陆柳
Dai Yuyan;Lu Liu(State Grid Electric Power Research Institute,SMEPC,Shanghai 200437,China)
出处
《计算机应用与软件》
北大核心
2025年第3期377-385,共9页
Computer Applications and Software
基金
国家电网公司总部科技项目(52094017001X)。
关键词
智能电表
时间故障传播图
支持向量机
攻击识别
Smart meter
Time fault propagation diagram
Support vector machine
Attack identification
作者简介
戴玉艳,工程师,主研领域:电能计量。;陆柳,经济师。
