入侵攻击下无线网络安全态势感知算法  

Wireless Network Security Situation Awareness Algorithm under Intrusion Attacks

作　　者：林广朋 李闯[2] LIN Guang-peng;LI Chuang(Information Network Center,Jilin Normal University,Siping Jilin 136000,China;Colledge of Computer,Jilin Normal University,Siping Jilin 136000,China)

机构地区：[1]吉林师范大学信息网络中心,吉林四平136000 [2]吉林师范大学计算机学院,吉林四平136000

出　　处：《计算机仿真》2023年第12期451-454,547,共5页Computer Simulation

摘　　要：采用目前算法感知入侵攻击下无线网络安全态势时,存在相对误差大、所用时间长、真阳性率和kappa值低的问题。提出入侵攻击下无线网络安全态势感知算法,首先将无线网络安全态势原始数据预处理,然后建立RBF神经网络预测模型,再结合HHGA算法和SA算法对RBF神经网络参数寻优,最后通过优化的RBF神经网络完成入侵攻击下的无线网络安全态势感知。实验结果表明,所提方法能够有效地降低相对误差、缩短所用时间、提高真阳性率和kappa值,具有较好的感知能力。Currently,some algorithms have some problems when sensing the security situation of wireless networks under intrusion attacks,such as large relative error,high time consumption,low true positive rate and low kappa value.Therefore,a wireless network security situation awareness algorithm under intrusion attack was presen⁃ted.Firstly,the original data of the wireless network security situation was preprocessed.Then,a prediction model based on RBF neural network was built.Secondly,RBF neural network parameters were optimized by the HHGA al⁃gorithm and SA algorithm.Finally,the wireless network security situation awareness under intrusion attack was com⁃pleted by the optimized RBF neural network.Experimental results show that the proposed method can effectively re⁃duce the relative error,shorten the time,improve the true positive rate and kappa value,and has good awareness a⁃bility.

关 键 词：入侵攻击 无线网络 安全态势感知 神经网络 网络参数优化 

分 类 号：TP393.08[自动化与计算机技术—计算机应用技术]