光接入网大数据恶意用户检测管理系统研究

Research on big data malicious user detection and management system in optical access network

各式各样日新月盛的新型应用在日常生活中不断涌现,由于目前网络安全监管机制并不健全,本文即以光接入网的恶意用户为研究对象,通过获取大量样本数据采集新特征及大数据分析,并与传统特征相结合,设定恶意用户和正常用户数据的特征区别并采用分类算法对恶意数据进行识别和判断。实验结果表明,本文的检测算法与传统算法相比准确率更高。

A variety of new applications are emerging in daily life.Due to the current network security supervision mechanism is not perfect,this paper takes malicious users of optical access network as the research object,through obtaining a large number of sample data,collecting new features and big data analysis,and combining with traditional features,it sets the characteristics of malicious users and normal users and adopts classification calculation Method to identify and judge malicious data.The experimental results show that the detection algorithm is more accurate than the traditional algorithm.