计算机工程与应用Issue(9)：81-84,4.DOI:10.3778/j.issn.1002-8331.1211-0239
基于 KNN-SVM 的网络安全态势评估模型
Assessment model of network security situation based on K Nearest Neighbor and Support Vector Machine
摘要
Abstract
In order to improve the network security situation assessment performance, this paper proposes assessment model (KNN-SVM)which integrates the K Nearest Neighbor with Support Vector Machine. The network security data set is input to the Support Vector Machine to learn and finds support vector set. When the distance between the sample of network security situ-ation and the optimal classification hyper plane is bigger than threshold, the Support Vector Machines are used to assess the net-work security situation, otherwise the K Nearest Neighbor is used to assess the network security situation to solve the defects and reduce the error rate of SVM. The simulation results show that, compared with the single SVM, KNN-SVM improves net-work security situation assessment accuracy and has more stable performance.关键词
网络安全态势/支持向量机/K 近邻算法/指标体系Key words
network security situation/Support Vector Machine(SVM)/K Nearest Neighbor(KNN)algorithm/index system分类
信息技术与安全科学引用本文复制引用
何永明..基于 KNN-SVM 的网络安全态势评估模型[J].计算机工程与应用,2013,(9):81-84,4.基金项目
浙江省教育厅项目(No.Y201226370) （No.Y201226370）
浙江省教科规项目(No.SCG286) （No.SCG286）
