based on the framework of network intrusion detection systems based on data mining , this paper devises an analyzer model of unsupervised learning.
本文在基于数据挖掘的网络入侵检测系统框架基础上设计了一个无导师学习的分析器模型。
secondly, the characteristics of the two different network intrusion detection systems based on negative selection algorithm and the combination of agents and immune system principles are introduced.
然后总结基于阴性选择算法以及主体与免疫系统原理相结合的两种不同的计算机入侵检测系统的特点;
current network intrusion detection systems have a fatal deficiency of being unable to detect new intrusive behaviors of unknown signatures and low intelligence level.
现有网络入侵检测系统的大都不能识别未知模式的入侵,智能水平低。