摘要
本文在分析国内外网络流量异常检测现状的基础上,针对多数异常检测模型实时性较差、检测率较低、误报率较高等问题,提出了一种新的基于分形技术和矢量量化的网络流量异常检测方法.理论分析表明,该方法具有较高的精度和较低的时间、空间复杂度,可以准确高效地检测出异常网络流量,并定位网络异常原因.
In this paper,with the research on the development survey of the network anomaly detection at home and abroad,a new algorithm for anomaly detection of network traffic based on fractal technology and vector quantization is proposed in view of most anomaly detection model with the poor real-time,the lower detection rate and the higher false positive rate.Theoretical analysis shows that this algorithm can achieve higher precision with less space and time complexity,and it can accurately and effectively discove...
出处
《邯郸学院学报》
2009年第3期73-76,共4页
Journal of Handan University
基金
河北省教育厅项目(项目编号:Z2009408)
关键词
分形
矢量量化
网络流量
异常检测
fractal
vector quantization
network traffic
anomaly detection