基于粒子群算法的网络流量异常检测方法  

The Anomaly Detection Method of Network Traffic Based on Particle Swarm Algorithm

作　　者：王戈 赵杰峰 WANG Ge;ZHAO Jiefeng(Computer Department,Kaifeng Vocational College of Culture and Arts,Kaifeng Henan 475000,China)

机构地区：[1]开封文化艺术职业学院计算机学院,河南开封475000

出　　处：《信息与电脑》2023年第10期82-84,共3页Information & Computer

摘　　要：针对网络流量异常检测结果误差较大的问题,提出基于粒子群算法的网络流量异常检测方法。首先,收集网络流量特征,根据熵值变化获取网络流量测度特征;其次,分析特征确定异常类别,完成网络流量异常的检测;最后,进行实验对比分析。实验结果表明,该方法能够检测出大部分网络流量异常现象,优于其他方法。Aiming at the problem of large error in network traffic anomaly detection results,a network traffic anomaly detection method based on particle swarm optimization algorithm is proposed.Firstly,network traffic characteristics are collected,and network traffic measurement characteristics are obtained according to the change of entropy;Secondly,analyze the characteristics to determine the type of anomaly,and complete the detection of network traffic anomaly;Finally,conduct experimental comparative analysis.Experimental results show that this method can detect most of the network traffic anomalies,and is superior to other methods.

关 键 词：网络流量异常 网络流量 粒子群算法 测度特征 

分 类 号：TP319[自动化与计算机技术—计算机软件与理论]