基于改进遗传神经网络的入侵检测模型

The intrusion detection model based on improved genetic neural network

本文针对目前基于BP神经网络的入侵检测已陷入局部极值和收敛速度慢等问题,提出一种基于改进的遗传算法和BP神经网络的混合入侵检测方法。仿真实验结果表明,此方法比单独使用BP神经网络的检测方法收敛速度更快,误差更小。

In view of problem such as local minima and slow convergence speed of present intrusion detection based on BP neural network, this article put forward a kind of intrusion detection method based on improved hybrid genetic algorithm and BP neural network.Simulation experiment results show that this method is faster is than single detection method using BP neural network, and the error is smaller.