逻辑回归模型下激光传感器网络安全态势感知  

Security situation awareness of laser sensor networks based on logistic regression model

作　　者：张佳[1] 韩健[1] 韩金玉[1] ZHANG Jia;HAN Jian;HAN Jinyu(Tianjin Sino-German University of Applied Sciences,Tianjin 300350,China)

机构地区：[1]天津中德应用技术大学,天津300350

出　　处：《激光杂志》2024年第2期174-180,共7页Laser Journal

基　　金：天津市教委科研计划项目(No.2020KJ083);天津市科技计划项目(No.22YDTPJC00790)。

摘　　要：为了分析不同威胁传播对激光传感器网络系统的影响,准确且全面评估系统的安全性,提出一种逻辑回归模型下激光传感器网络安全态势感知方法。将邻域粗糙集和逻辑回归模型结合,提取激光传感器网络安全态势要素。通过分析获取其不同要素的非时间序列特点,采用径向基函数(Radial Basis Function,RBF)神经网络获取网络安全态势值的非线性映射关系,构建激光传感器网络安全态势感知模型,引入混合递阶遗传算法对模型求解处理,实现网络安全态势感知。实验结果表明,所提方法获取激光传感器网络安全态势精度为96.4%,其安全态势值与实际值的误差保持在-3~3,可以获取精准的激光传感器网络安全态势变化情况,表明该方法具有一定的应用价值。In order to analyze the impact of different threat propagation on the laser sensor network system,and accurately and comprehensively evaluate the security of the system,a method of laser sensor network security situation awareness under the logic regression model is proposed.The neighborhood rough set and logical regression model are combined to extract the security situation elements of the laser sensor network.By analyzing the non time series characteristics of different elements,the RBF neural network is used to obtain the nonlinear mapping relationship of network security situation values,and the laser sensor network security situation awareness model is constructed.The hybrid hierarchical genetic algorithm is introduced to solve the model to achieve network security situation awareness.The experimental results show that the accuracy of the proposed method to obtain the security situation of the laser sensor network is 96.4%,and the error between the security situation value and the actual value is kept at-3~3,which can obtain accurate changes in the security situation of the laser sensor network,indicating that the method has certain application value.

关 键 词：逻辑回归模型 激光传感器网络 安全态势感知 RBF神经网络 

分 类 号：TN915.08[电子电信—通信与信息系统]