作 者: ;
机构地区: 河南财经学院计算机与信息工程学院
出 处: 《河南科学》 2005年第1期91-93,共3页
摘 要: 传统的入侵检测系统(IDS)建立训练数据集时消耗的成本都非常高,自适应模型产生系统能够有效地解决这一问题,它可以为基于数据挖掘的入侵检测系统自动建立检测模型,而无需再用人工对数据做出标识。本文介绍了该模型的体系结构,并对其工作原理进行了分析,在此基础上建立自适应入侵检测模型。 The costs of constructing data sets to train misuse model and anomaly model are usually very expensive for conventional intrusion detection systems. The data mining-based adaptive model generation systems provides an effective solution to these, by automatically collecting data to train the detection models. In this paper, the architecture and the detection principle of adaptive model generation systems are studied, then the adaptive model for intrusion detection of computer network is established.
领 域: [自动化与计算机技术] [自动化与计算机技术]