基于数据挖掘的网络入侵检测系统研究

The Research of the Network Intrusion Detection System Based on Data Mining

现有入侵检测系统一般存在着自适应性差、误报、漏报问题、数据过载等问题。面基于数据挖掘的入侵检测系统智能性好,自动化程度高、检测效率高、自适应能力强,从而使入侵检测系统具有更好的自学习、自适应和自我扩展的能力。本文提出了一种基于数据挖掘的网络入侵检测系统模型。

Current intrusion detection system in general there is poor adaptability, false, omitted the issue of data overload. Surface- based data mining intrusion detection system of intelligent, highly automated, efficieut detection, adaptive ability, so that the intrusion detection system with better self-learning, adaptive and self-expansion. In this paper, a data mining-based network intrusion detection system model is introduced.