IDE-SVM算法及其在物联网物理层安全中的应用  

IDE-SVM algorithm and it's usage in physical layer security method for IoT

作　　者：王强 朱晨鸣 潘甦[2] 秦玉玺 WANG Qiang;ZHU Chenming;PAN Su;QIN Yuxi(China Information Consulting and Designing Institute Co.,Ltd.,Nanjing 210019,China;Nanjing University of Posts and Telecommunications,Nanjing 210003,China)

机构地区：[1]中通服咨询设计研究院有限公司,江苏南京210019 [2]南京邮电大学,江苏南京210003

出　　处：《西北工业大学学报》2024年第5期882-890,共9页Journal of Northwestern Polytechnical University

基　　金：国家自然科学基金(62071244)资助。

摘　　要：针对支持向量机(support vector machine,SVM)算法参数选择没有标准的问题,提出了一种基于综合改进差分进化算法(improve differential evolution,IDE)的参数优化选择方法,以分类错误率最小为优化准则,利用改进的差分进化算法实现SVM参数的组合优化,获得了一种更高分类精度的SVM算法。为了避免基本DE算法在求解SVM参数选择问题时陷入局部最优,提高DE算法的搜索效率,提出了一种改进差分进化算法,通过使用圆弧函数对变异缩放比例因子F以及交叉概率因子R进行自适应控制,同时结合随机新生个体替换操作,得到一种收敛速度更快、精度更高的DE算法。在此基础上,提出了一种基于IDE-SVM物联网物理层安全方法。实验结果表明基于改进后SVM算法的物理层安全方法认证准确率更高。To address the problem that there is no standard for the parameter selection of support vector machine(SVM)algorithm,a parameter optimization selection method based on the integrated improved differential evolution(IDE)algorithm is proposed,which uses the minimization of the classification error rate as the optimization criterion and the improved differential evolution algorithm to optimize the combination of SVM parameters to obtain an SVM algorithm with higher classification accuracy.At the same time,to avoid the basic DE algorithm from falling into local optimum when solving the SVM parameter selection problem and to improve the search efficiency of the DE algorithm.In this paper,an improved differential evolutionary algorithm is proposed to obtain a DE algorithm with faster convergence and higher accuracy by using the circular arc function for adaptive control of the variance scaling factor F and the crossover probability factor R,combining with the random newborn individual replacement operation.Based on this,an IDE-SVM IoT physical layer security method based on IDE-SVM is proposed.The experimental results show that the authentication accuracy of the physical layer security method based on the improved SVM algorithm is higher than others.

关 键 词：物理层安全 支持向量机 差分进化 参数优化 

分 类 号：TN918.91[电子电信—通信与信息系统]