基于约简数据集的网络入侵检测技术研究

Research on Network Intrusion Detection Technology based on Reduced Data Set

网络入侵检测技术是网络安全的重要内容,而对于数据挖掘中的样本约简,主要是从缩减数据集中的样本数量上来实现数据挖掘成本的有效降低。本文将从基于类中心的分层样本约简方法入手,探讨数据集中相对于其他类别的数据子集指标,并从原始数据集中选取样本子集,实现对入侵检测模型的构建。

The network intrusion detection technology is an important part of network security,and for the sample reduction in data mining,it is mainly from the reduction in the number of data samples to achieve effective cost reduction in data mining. This paper,starting from the layered sample reduction method based on classified center,explores on other classes of data index,and from the original data selected from the sample subset,realizes the construction of intrusion detection model.