基于机器学习的电力系统稳定通信终端安全身份认证方法  

Secure Identity Authentication Method for Power System Stable Communication Terminal Based on Machine Learning

作　　者：梁懿 王秋琳 LIANG Yi;WANG Qiulin(Fujian Yirong Information Technology Co.,Ltd.,Fuzhou 350003,China)

机构地区：[1]福建亿榕信息技术有限公司,福建福州350003

出　　处：《微型电脑应用》2024年第4期166-168,177,共4页Microcomputer Applications

摘　　要：针对电力系统稳定通信终端安全身份认证的认证准确率和认证效率较低的问题,设计一种基于机器学习的电力系统稳定通信终端安全身份认证方法。完善身份认证的公钥基础设施(PKI),定义了内部组成、传输流程以及各部分功能;结合人工神经网络与极限学习机算法,改进了电力系统稳定通信终端认证基础设施;建立电力系统稳定通信安全身份认证模型,设计了安全身份认证流程,实现安全身份认证。算例分析结果表明,设计方法在外界条件改变的情况下性能稳定,认证准确率始终高于69.13%,身份认证的可靠性较强。Aiming at the low authentication accuracy and efficiency of security identity authentication of power system stability communication terminal,a security identity authentication method of power system stability communication terminal based on machine learning is designed.This paper improves the public key infrastructure(PKI)for identity authentication,and defines the internal composition,transmission process and functions of each part.By combining artificial neural network and limit learning machine algorithm,This paper improves the authentication infrastructure of power system stable communication terminal.This paper also establishs the security identity authentication model of power system stable communication,designs the security identity authentication process and realizes the security identity authentication.The results of example analysis show that the performance of the design method is stable when the external conditions change,the authentication accuracy is always higher than 69.13%,and the reliability of identity authentication is strong.

关 键 词：机器学习 人工神经网络 电力系统 稳定通信终端 安全身份认证 

分 类 号：N918[自然科学总论] TP181[自动化与计算机技术—控制理论与控制工程]