基于网络态势数据挖掘的漏洞检测系统设计

Design of vulnerability detection system based on network situation data mining

传统方法在检测网络漏洞时,过程较为复杂,且检测存在局限性、精准度低的问题,设计基于网络态势数据挖掘的漏洞检测系统。通过分析数据准备、挖掘与评估展示三个步骤对风险数据做聚类处理,为漏洞数据的挖掘提供帮助,减少运算量,并针对聚类结果采用关联挖掘方法做聚类跟踪,明确漏洞范围;分析检测系统特点,设计系统的总体结构框架,建立检测数据库;分别从静态模块、漏洞扫描与页面展示模块三方面实现漏洞检测系统的设计。仿真实验结果表明,该系统实现了高检测效率、低错误率的漏洞自动化检测,为解决各类网络安全问题奠定了基础。

Since the traditional methods are limited and inaccurate,and has a complex process in detecting network vulnerabilities,a vulnerability detection system based on network situation data mining is designed.In the design,the cluster processing for risk data is carried out by analyzing the three steps of data preparation,data mining and evaluation to provide help for the mining of vulnerability data and reduce the computation burden for the vulnerability data.Moreover,the association mining method is adopted to implement cluster tracking according to the clustering results,so as to define the scope of the vulnerability.The characteristics of the detection system are analyzed.The overall framework of the system is designed.The detection database is established.The design of the vulnerability detection system is realized in the aspects of static module,vulnerability scanning module and page display module.The simulation results show that the proposed system can realize the automatic vulnerability detection with high detection efficiency and low error rate,which lays a foundation for solving various network security problems.