分层神经网络在入侵检测系统中的应用

Intrusion detection based on hierarchical neural network

入侵检测技术是提高网络安全的重要手段之一,旨在利用分层神经网络解决入侵检测问题。针对入侵检测研究的通用审计数据集,首先将数据进行预处理以便运算;其次利用RBF网络实现粗检测;再次利用Elman BP网络进行细检测,从而实现分层神经网络的入侵检测;最后在MATLAB平台下进行仿真实验,仿真结果表明,分层神经网络结构在入侵检测中体现出良好的特性。

Intrusion detection is one of important ways to improve network security,and is a main research topic in computer field.The benchmark dataset commonly used in the research of intrusion detection is adopted.Firstly,data are changed into the appropriate type for simulations;Secondly RBF network is used for raw detection;Thirdly Elman BP network is used for advanced detection;Lastly a lot of simulation results are gained from MATLAB platform,and display that hierarchical network is fit for intrusion detection.