摘要
传统的漏洞定位方法定位精度较低,为此,提出一种机房网络安全漏洞自动挖掘与定位方法。首先,设计机房网络安全态势感知模型,利用攻击关联性矩阵和网络态势评估函数,以精准感知机房网络的安全态势。然后,利用信息提取引擎和关联分析子模块,并结合优化的目标函数和皮尔逊相关系数,对机房网络安全的漏洞进行自动挖掘。最后,建立漏洞数据库,并通过构建安全漏洞弧序列,引入蚁群算法,定位安全漏洞位置具体的网络节点。结果表明,该方法能够有效提升机房网络安全漏洞的定位精度,在不同场景下均无漏检和误检现象,具有实际应用价值。
Traditional vulnerability positioning methods exhibit relatively low positioning accuracy,and to address this,an automatic mining and positioning method for network security vulnerabilities in computer rooms is proposed.Firstly,a network security situation awareness model for computer rooms is designed,utilizing an attack correlation matrix and a network situation assessment function to accurately perceive the security situation of the network in computer rooms.Then,an information extraction engine and a correlation analysis submodule are employed,combined with an optimized objective function and Pearson correlation coefficient,to automatically mine vulnerabilities in network security in computer rooms.Finally,a vulnerability database is established,and by constructing security vulnerability arc sequences and introducing an Ant Colony Optimization,the specific network nodes where security vulnerabilities are located are positioned.The results indicate that this method can effectively enhance the positioning accuracy of network security vulnerabilities in computer rooms,with no instances of missed or false detections under different scenarios,demonstrating practical application value.
作者
刘青
LIU Qing(Shanxi Open University,Taiyuan,Shanxi 030027,China)
出处
《自动化应用》
2025年第18期270-272,共3页
Automation Application
关键词
机房网络安全
安全态势感知
漏洞自动挖掘
漏洞定位
漏洞数据库
network security in computer room
security situation awareness
automatic vulnerability mining
vulnerability positioning
vulnerability database
