一种基于粗糙集和决策树的入侵检测数据处理方法

A Method for Data Analyzing of Intrusion Detection Based on Rough Set and Decision Tree

本文对入侵检测系统采集的海量数据,首先进行抽样分析,然后使用粗糙集理论的属性约简方法对数据进行预处理,再运用决策树ID3算法进行归纳学习,得到入侵检测数据的决策规则,进而判断流经网络的数据包的安全性,最后加以编程实现数据挖掘的自动化。粗糙集和决策树学习方法在处理问题的过程中是基于决策系统本身的信息,不需要其他人为的经验知识,相比其他数据挖掘方法来说,更具有客观性和实用性。

Intrusion detection system （IDS） is an active measure using attacks as a means of defense. It lays emphasis on attack inside network. Aiming to the intrusion detection data, this article makes a sample analysis, and then uses the attributes reduction method of rough set theory for data preprocessing, and learns the data with the method of decision tree ID3 arithmetic. Consequently, the decision rules of the intrusion data can be obtained so as to estimate the security of the data packets which move through the network..