首页 | 本学科首页   官方微博 | 高级检索  
     

一种基于自回归模型的网络异常检测方法
引用本文:余朝华,齐德昱,陈锐忠. 一种基于自回归模型的网络异常检测方法[J]. 计算机应用, 2012, 32(Z1): 5-7
作者姓名:余朝华  齐德昱  陈锐忠
作者单位:1. 广州市水务局机关服务中心,广州,510640
2. 华南理工大学计算机系统研究所,广州,510640
摘    要:
随着网络技术的不断发展,计算机病毒、网络攻击等问题也日益严峻.维护网络的安全和稳定,是一个亟须解决的问题.针对该问题,介绍了一种基于自回归模型的网络异常检测方法,该方法将局部的网络流量看作统计学上近似的平稳.OPNET上的仿真实验表明,该方法能有效检测出网络异常,误报率低.

关 键 词:异常检测  自回归模型  Matlab  OPNET仿真

Network anomaly detection approach based on autoregression model
YU Chao-hua , QI De-yu , CHEN Rui-zhong. Network anomaly detection approach based on autoregression model[J]. Journal of Computer Applications, 2012, 32(Z1): 5-7
Authors:YU Chao-hua    QI De-yu    CHEN Rui-zhong
Affiliation:1.Organs Service Center,Guangzhou Water Affairs Bureau,Guangzhou Guangdong 510640,China; 2.Research Institute of Computer Systems,South China University of Technology,Guangzhou Guangdong 510640,China)
Abstract:
With the development of network technology,it is more and more serious to deal with the computer virus and network attacks.It is critical to maintain the security and stableness so as to ensure the efficiency and proper operation of the network.To solve this problem,This paper introduced a method of network abnormity detection based on autoregression model.It assumes the local network traffic is statistically steady.The simulation on OPNET demonstrates this method can effectively detect network anomalies and its misstatement rate is low.
Keywords:abnormity detection  autoregression model  Matlab  OPNET simulation
本文献已被 CNKI 万方数据 等数据库收录!
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号