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基于麻雀搜索算法的电力数据中心网络入侵安全检测方法

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中心网络体系能否准确检测出电力入侵数据的行为等级,决定了电力网络是否具有持续稳定运行的能力.为更好维护电力网络的运行稳定性,对基于麻雀搜索算法的电力数据中心网络入侵安全检测方法展开研究,推导电力数据入侵行为判定标准,实现基于麻雀搜索算法的电力数据入侵行为预测.搭建分布式检测框架,通过分析电力入侵数据安全性等级的方式,生成具体的关联性安全检测规则,完成基于麻雀搜索算法的电力数据中心网络入侵安全检测方法的设计.试验结果表明,麻雀搜索算法作用下,风险性等级条件与电力入侵数据的实际行为等级完全相同,符合准确检测的应用需求,能够较好维护电力网络的运行稳定性.
Network Intrusion Security Detection Method of Power Data Center Network Based on Sparrow Search Algorithm
Whether the central network system can accurately detect the behavior level of power intrusion data determines whether the power network has the ability to operate continuously and stably.To better maintain the operational stability of the power network,the research was conducted on the intrusion security detection method for power data center networks based on the sparrow search algorithm.The criteria for determining the intrusion behavior of power data and the prediction of power data intrusion behavior achieved based on the sparrow search algorithm.A distributed detection framework was built,the security level of power intrusion data was analyzed,the specific association security detection rules were generated,and the design of a network intrusion security detection method was completed for power data center based on the sparrow search algorithm.The experimental results show that under the action of the sparrow search algorithm,the risk level conditions are exactly the same as the actual behavior level of the power intrusion data,which meets the application requirements of accurate detection and can better maintain the stability of the power network operation.

sparrow search algorithmpower datacentral networkintrusion detectiondistributed frameworkassociation rulesbehavior hier-archy

张婧、范海燕、丁鲁彬、刘凯华、陈杰

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国网青海海北供电公司,青海海北 812200

山东工商学院,山东烟台 264000

济南大学,山东济南 250000

山东科技大学,山东青岛 266000

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麻雀搜索算法 电力数据 中心网络 入侵检测 分布式框架 关联规则 行为等级

2024

电气自动化
上海电气自动化设计研究所有限公司 上海市自动化学会

电气自动化

CSTPCD
影响因子:0.377
ISSN:1000-3886
年,卷(期):2024.46(6)