基于反向传播神经网络的微电网恶意信息数据检测系统设计  

Design of micro⁃grid′s malicious information data detection system based on back propagation neural network

作　　者：岳俊英 李存斌 YUE Junying;LI Cunbin(North China Electric Power University,Beijing 102206,China;College of Computer Science and Technology,Inner Mongolia Normal University,Hohhot 010022,China)

机构地区：[1]华北电力大学,北京102206 [2]内蒙古师范大学计算机科学技术学院,内蒙古呼和浩特010022

出　　处：《现代电子技术》2021年第18期17-21,共5页Modern Electronics Technique

基　　金：国家自然科学基金项目(71671065);国家电网公司科技项目(5204BB1600CP)。

摘　　要：为解决微电网容易遭受到恶意信息数据注入攻击,而导致微电网安全性下降的问题,文中设计一种基于反向传播神经网络的微电网恶意信息数据检测系统。首先,完成系统硬件设计,该系统硬件由数据处理模块、终端安全模块、敏感数据监测模块、访问监视模块、应用系统集成模块组成。然后,采用优化后的反向传播神经网络提取微电网恶意信息数据特征,将待检测样本数据特征与恶意信息数据特征进行匹配,获取检测结果,实现微电网恶意信息数据检测系统设计。实践表明,该系统的检测时间短,检测结果查全率与查准率高于优化反向传播神经网络学习过程,可见,该系统具有很强的实用性。In order to solve the problem that micro⁃grid is vulnerable to malicious information data injection attack,which leads to the decline of micro⁃grid security,a micro⁃grid′s malicious information data detection system based on back propagation neural network is designed.The hardware design of the system is completed.The hardware of the system consists of data processing module,terminal security module,sensitive data monitoring module,access monitoring module and application system integration module.The optimized back propagation neural network is used to extract the features of the micro⁃grid malicious information data.And the data features of the samples under detection are matched with the data features of the malicious information to obtain the detection results,so as to realize the design of the micro⁃grid malicious information data detection system.The practice indicates that the detection time of the system is short,and the recall and precision of the detection results are higher than that of the optimized BP neural network learning process.It can be seen that the system has strong practicability.

关 键 词：恶意信息数据检测 神经网络 反向传播 微电网 系统设计 仿真实验 

分 类 号：TN911.233.4[电子电信—通信与信息系统] TM727[电子电信—信息与通信工程]