摘要
由于智慧网络环境具有复杂性和动态性,且存在大量的未知访问请求,没有预先定义的信誉信息,增加了安全性预警的难度。为此,提出智慧网络大规模未知访问源安全性预警方法。利用提升小波变换方法对未知访问源的数据包展开降噪处理,建立自动免疫抗体,提取未知访问源数据包特征,识别未知访问源异常,采用模糊综合评价方法对异常访问源的安全性展开评价,根据评价结果确定访问源的风险等级,实现安全性预警。仿真结果表明,所提方法的降噪效果好,可以准确获取未知访问源的风险值变化情况,且预警精度高。
At present,the intelligent network environment is complex and dynamic.There are a large number of unknown access requests and there is no predefined reputation information,which increases the difficulty of security early warning.Therefore,a security early warning method for large-scale unknown access sources in intelligent networks was proposed.At first,the improved wavelet transform method was adopted to perform the noise reduction on packets of unknown access sources and construct automatic immune antibodies,thus extracting packet features of unknown access sources and identifying the anomalies.Then,a fuzzy comprehensive evaluation method was used to evaluate the security of abnormal access sources,and thus to determine the risk level.Finally,the security early warning was achieved.Simulation results show that the proposed method has good noise reduction effect and high early-warning precision,so it accurately obtains the risk change of unknown access source.
作者
刘凯
王恒
LIU Kai;WANG Heng(Ningxia Medical University,Yinchuan Ningxia 750004,China;School of Information Engineering,Ningxia University,Yinchuan Ningxia 750021,China)
出处
《计算机仿真》
2024年第8期404-407,412,共5页
Computer Simulation
基金
教育部产学合作协同育人项目(220503175115119)。
关键词
智慧网络
提升小波变换方法
异常检测
未知访问源
安全性预警
Intelligent network
Improved wavelet transform method
Abnormal detection
Unknown access source
Security early-warning
