基于支持向量机的无线网络入侵特征提取算法  

Algorithm of Wireless Network Intrusion Feature Extraction Based on Support Vector Machine

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作  者:陈金鑫 Chen Jinxin(West Anhui University, Lu’an 237012, China)

机构地区:[1]皖西学院,安徽六安237012

出  处:《黑龙江科学》2021年第12期34-35,38,共3页Heilongjiang Science

摘  要:为解决传统方法在网络入侵特征提取过程中存在的特征数据漏检率较高的问题,提出基于支持向量机的无线网络入侵特征提取算法。建立入侵特征提取原则,即全面性、层次性、独立性,采用支持向量机筛选入侵特征指标,通过构建入侵特征提取矩阵,实现对无线网络入侵特征的提取。实验结果表明,所提算法能够降低特征漏检率,使提取结果具有可靠性,有利于建立无线网络安全环境,为网络安全检测技术的发展提供基础。In order to solve the problem of high omission ratio of characteristic data in traditional method application in network intrusion extraction process,the algorithm of wireless network intrusion feature extraction based on support vector machine is proposed.Intrusion feature extraction principle is established,i.e.comprehensiveness,hierarchy and independency.Intrusion index is selected through support vector machine.Through the construction of instruction feature,matrix is extracted to achieve the extraction of wireless network intrusion feature.The experiment results indicate that the algorithm can reduce the feature omission ratio,and make the intrusion results reliable.So it is beneficial to establish wireless network security environment,and provides foundation for the development of network security test technology.

关 键 词:支持向量机 无线网络 特征提取 层次性原则 

分 类 号:TP393[自动化与计算机技术—计算机应用技术]

 

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