基于自适应性模型的入侵检测系统研究

Study of Intrusion Detection System Based on Adaptive Model

适应性模型是一种自动建立的基于数据挖掘的入侵检测系统检测模型。在利用入侵检测传感器收集相同数据的同时,系统自动建立适应性模型。由于不需要建立训练集,从而减少了配置入侵检测系统的花费。本文提出了一种自动模型及其系统结构的有效实现,并用算法自动建立了在噪声数据上的异常检测模型。

Adaptive model is a detecting model which is automatically built of intrusion detection systems based on data-mining. While using the same data collected by intrusion detection sensors, adaptive model is automatically built. This reduces the configuration cost of intrusion detecting system because it dose not require to build training sets. An automatic model and its system architecture are presented, and an algorithm that automatically builds abnormally detecting models on noisy data is realized.