基于深度神经网络的无线通信网络异常自适应辨识研究  

Study on Abnormal Adaptive Identification of Wireless Communication Network Based on Deep Neural Network

作　　者：王艳旗 杨园园 WANG Yanqi;YANG Yuanyuan(School of Information and Electronic Engineering,Shangqiu Institute of Technology,Shangqiu 476000,China)

机构地区：[1]商丘工学院信息与电子工程学院,河南商丘476000

出　　处：《通信电源技术》2025年第4期25-27,共3页Telecom Power Technology

摘　　要：现有的辨识方法对网络攻击行为的误识率高,导致辨识效果较差,为此研究基于深度神经网络的无线通信网络异常自适应辨识。建立无线通信网络空间,并在该空间中检索粒子群以进行数据采样。通过深度神经网络对采样后的数据进行特征提取,并引进K算法聚类处理数据特征,将其与无线通信网络异常数据特征进行对比,以此完成无线通信网络异常自适应辨识。实验结果表明,所设计的基于深度神经网络的辨识方法误识率小于5%,误识程度最低,能够显著提升网络安全性能,展现出良好的识别效果。The high misidentification rate of existing identification methods for network attack behavior,the identification effect is poor.Therefore,research is being conducted on wireless communication network anomaly adaptive identification based on deep neural networks.Establish a wireless communication network space and retrieve particle swarm optimization for data sampling in that space.By using deep neural networks to extract features from sampled data,and introducing the K algorithm to cluster the data features,it is compared with the abnormal data features of wireless communication networks to achieve adaptive identification of wireless communication network anomalies.The experimental results show that the designed identification method based on deep neural networks has an error rate of less than 5%and the lowest degree of error,can significantly improve network security performance and demonstrate good recognition performance.

关 键 词：深度神经网络 无线通信 异常 辨识 通信网络 

分 类 号：TN92[电子电信—通信与信息系统] TP183[电子电信—信息与通信工程]