大规模多维多层次网络安全漏洞自动检测技术

Automatic Detection Technology for Security Vulnerabilities in Large-Scale, Multi-Dimensional and Multi-Level Networks

针对网络运行异常数据的检索步长呈现模糊性,导致数据分析失真,漏洞检测不准的问题,提出了针对大规模多维多层次网络的安全漏洞检测方法。将网络结构调整为一个完整的无向模型,分析大规模多维多层次网络数据结构,根据分析结果确定检索步长,完成多维多层次网络数据分析。利用安全态势感知进行网络检测,计算截获的网络信号数据,分析数据信号波动,根据波动情况实现漏洞检测。实验结果表明:所提方法的大规模多维多层次网络安全漏洞检测时间低于90 ms,检出率低于0.3%,具有较好的应用效果。

A security vulnerability detection method for large-scale multidimensional and multi-level networks has been proposed.Adjust the network structure to a complete undirected model,analyze the large-scale multidimensional and multi-level network data structure,determine the search step size based on the analysis results,and complete the multidimensional and multi-level network data analysis.Using security situational awareness for network detection,calculating intercepted network signal data,analyzing data signal fluctuations,and implementing vulnerability detection based on fluctuations.The experimental results show that the proposed method has a large-scale,multi-dimensional,and multi-level network security vulnerability detection time of less than 90ms,with a detection rate of less than 0.3%,and has good application effects.