基于贝叶斯的入侵检测模型与仿真研究

The Intrusion Detection Model and Simulation Study Based on the Bayesian

本文提出了一种基于贝叶斯的网络入侵检测模型.首先,使用主成分分析法提取网络数据包关键属性、消除冗余属性、降低维数,再用贝叶斯分类器进行分类.结果表明,该模型不但提高了入侵检测的效率,而且也加快了检测速度,更适合当前的复杂网络检测.

This paper proposes a network intrusion detection model based on Bayesian . First , the principal component analysis （PCA） was used to extract the key ability ,eliminate the redundant attributes ,reduce the data dimension ,then use the Bayesian classifier to classify .The simulation results show that the model improves the efficiency of the intrusion detection and speed up the detection speed , and is suitable for the current complex network intrusion detection .