基于数据发掘的入侵检测建模

Building Intrusion Detection Model Based on Data Mining

所谓数据发掘DataMining,就是从大量数据中发掘新的、有用模式的过程。把数据发掘用于入侵检测,可以从审计数据中发掘出具有系统活动特征的有用的模式,以指导、训练数据的收集和特征的选择和建立活动分类机制。为此,进行了基于DM的入侵检测模型的建立过程和所用算法的研究。

:Data mining is a process of identifying novel and potentially useful patterns in data.Using DM technique to intrusion detection,the useful patterns of system behavior features can be discovered in au-dit data.The discovered patterns can guide the audit data gathering and feature selection and build the behavior classified system.In this paper we study the process of building ID model and the algorithms that were used.