大数据分析的漏洞检测方案设计

Design of Vulnerability Detection Scheme for Large Data Analysis

数据驱动决策的前景现在得到了广泛认可,人们对“大数据”的概念越来越感兴趣,但是随着网络数据流量的增加,移动终端和应用程序的普及,信息传播速率的加快,数据的安全漏洞也越来越大。传统的漏洞检测方法已不能满足需求,采用大数据分析技术来检测漏洞,对提升网络安全具有重要的意义。基于此,提出一种大数据分析漏洞检测技术,通过对网络的实时数据流进行分析,并利用漏洞的攻击特征从而提高漏洞检测效率。通过实验验证,取得较好的检测性能和运行效率。

The prospect of data-driven decision-making is now widely recognized.People are more and more interested in the concept of"big data".However,with the increase of network data traffic,the popularity of mobile terminals and applications,the speed of information dissemination,and the security vulnerabilities of data are also growing.Traditional vulnerability detection methods can’t meet the needs,so it is of great significance to improve network security to use large data analysis technology to detect vulnerabilities.A vulnerability detection technology based on large data analysis is proposed,which can improve the efficiency of vulnerability detection by analyzing the real-time data flow of the network and exploiting the vulnerability attack characteristics.Through experimental verification,better detection performance and operation efficiency are achieved.