人工神经网络下5G通信网络信息安全防护研究  

Information security protection of 5G communicationnetwork based on artificial neural network

作　　者：沈毅波[1] 林志维[1] SHEN Yi-bo;LIN Zhi-wei(College of Electronics and Information Engineering,Zhangzhou Institute of Technology,Zhangzhou,Fujian 363000,China)

机构地区：[1]漳州职业技术学院电子信息学院,福建漳州363000

出　　处：《宁德师范学院学报（自然科学版）》2023年第1期31-37,共7页Journal of Ningde Normal University(Natural Science)

基　　金：福建省教育厅中青年教育科研项目(JAT210845).

摘　　要：网络应用、服务与终端用户呈现暴增趋势,为网络信息安全带来极大的威胁.而网络信息安全是保证其稳定运行的基础与前提,为此,提出基于人工神经网络的5G通信网络信息安全防护方法.明确5G通信网络信息安全问题成因,构建通信用户实名认证架构,在源头验证用户身份信息,选取DES算法(对称加密技术)加密处理网络信息.基于人工神经网络创建网络信息分类器,将网络信息集合输入至训练好的分类器中,即可完成异常网络信息的检测.实验结果显示在不同场景下,应用提出方法获得的异常网络信息检测时延更短,网络信息安全参量取值更大,证实提出方法应用性能较佳.Network applications,services and end users are increasing rapidly,which poses a great threat to net⁃work information security.Network information security is the basis and premise to ensure its stable operation.Therefore,an information security protection method of 5G communication network based on artificial neural network is proposed.We clarify the causes of 5G communication network information security problems,build a communication user real name authentication architecture,verify the user′s identity information at the source,select DES algorithm(symmetric encryption technology)to encrypt and process the network informa⁃tion,create a network information classifier based on artificial neural network,and input the network informa⁃tion set into the trained classifier to complete the detection of abnormal network information.The experimental results show that in different scenarios,the detection delay of abnormal network information obtained by the proposed method is shorter and the value of network information security parameters is larger,which proves that the application performance of the proposed method is better.

关 键 词：5G通信网络 信息安全 网络信息 人工神经网络 安全防护 安全评价 

分 类 号：TN915.08[电子电信—通信与信息系统]