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：吉志强 吕亚玲 JI Zhiqiang;LYU Yaling(School of Computer Science and Mathematics,Anyang University,Anyang Henan 455000,China;School of Foreign Languages,Anyang University,Anyang Henan 455000,China)

机构地区：[1]安阳学院计算机科学与数学学院,河南安阳455000 [2]安阳学院外国语学院,河南安阳455000

出　　处：《信息与电脑》2023年第14期103-105,共3页Information & Computer

摘　　要：由于网络流量异常数据具有维数大和冗余度高等特征,导致传统方法的检测精度较低,为此提出基于粒子群算法的网络流量异常检测方法。首先,采集网络流量数据,并进行外部参数提取与流量过滤等预处理;其次,基于粒子群算法优化分类规则的编码方案;最后,进行实验分析。实验结果表明,该方法的性能优于对照组,能够最大限度地保障检测结果的准确性。Due to the large dimension and high redundancy of network traffic anomaly data,the detection accuracy of traditional methods is low.Therefore,a network traffic anomaly detection method based on particle swarm optimization algorithm is proposed.Firstly,collect network traffic data,and carry out external parameter extraction and traffic filtering and other pretreatment.Secondly,optimize the encoding scheme of classification rules based on particle swarm optimization algorithm.Finally,conduct experimental analysis.The experimental results show that the performance of this method is superior to that of the control group,and it can maximize the accuracy of the detection results.

关 键 词：粒子群算法 网络流量 异常检测 检测方法 

分 类 号：TP39[自动化与计算机技术—计算机应用技术]