基于数据挖掘的自适应入侵检测模型研究

Research on Adaptive Intrusion Detection Model Based on Data Mining

针对当前入侵检测系统的局限性,提出将数据挖掘技术引入到入侵检测中,研究了Apriori关联算法、ID3分类算法和FHCAM聚类算法在入侵检测中的应用,建立了一个基于数据挖掘的自适应入侵检测模型。该模型能够识别已知和未知的入侵,降低检测的漏报率和误报率,有效的提高检测效率。

To solve the problems of current intrusion detection systems, the methods and technologies of data mining are applied to intrusion detection. The Apriori algorithm, the ID3 algorithm and the FHCAM algorithm are re-searched for application to intrusion detection, an adaptive model of intrusion detection based on data mining is estab-lished. This model can recognize known or unknown intrusions of the network and decrease the false detection rate of the intrusion detection, so the efficiency of all kinds of intrusion detection is improved.