基于改进支持向量机的网络安全态势评估模型的研究  

Research on Network Security Situation Assessment Model Based on Improved Support Vector Machine

作　　者：陈小永[1] 赵飞 CHEN Xiaoyong;ZHAO Fei(School of Software Engineering,Anhui College of Electronic Information Technology,Bengbu 233000,China;School of Computer Science and Technology,Anhui University of Technology,Ma’anshan 243032,China)

机构地区：[1]安徽电子信息职业技术学院软件工程学院,安徽蚌埠233000 [2]安徽工业大学计算机科学与技术学院,安徽马鞍山243032

出　　处：《安阳师范学院学报》2025年第2期17-22,共6页Journal of Anyang Normal University

基　　金：2024年度安徽省高校自然科学研究重点项目“基于图神经网络GNN的漏洞检测算法研究与应用”(项目编号:2024AH050095);安徽省质量工程项目(项目编号:2022kcsz020)。

摘　　要：在信息安全领域,网络安全态势评估已成为信息安全领域中的一个主要研究方向。在以往研究基础上,将支持向量机与鱼群算法相结合,研究面向信息系统的信息安全态势评估模型,提出一种基于遗传算法的优化方法,并将其应用于支持向量机中的参数C、参数g的搜索。利用SVM进行分级,选择径向基函数作为支持向量机的核心,采用基于遗传算法的多目标优化算法,并与传统的多目标优化算法进行了比较。结果显示,基于鱼群算法的改进支持向量机信息融合方法能够对现有的信息系统进行快速、准确和实时的计算机网络安全态势评估,具有一定的研究及应用价值。In the field of information security,network security situation assessment has gradually become a main research direction in the field of information security.On the basis of previous research,the information security situation assessment model for information system is studied by combining support vector machine and fish swarm algorithm,and an optimization method based on genetic algorithm is proposed,and it is applied to search parameters and parameters in support vector machine.Svc is used for classification,radial basis function is chosen as the core of support vector machine,and multi–objective optimization algorithm based on genetic algorithm is adopted,and the methed is compared with traditional multi–objective optimization algorithm.The results show that the improved support vector machine information fusion method based on fish swarm algorithm can evaluate the security situation of computer network quickly,accurately and in real time,and has certain research and application value.

关 键 词：计算机网络安全 态势评估 支持向量机 鱼群算法 

分 类 号：TP393.08[自动化与计算机技术—计算机应用技术]