Intrusion Detection Based on RBF Neural Network
暂无分享,去创建一个
Radial Basis Function (RBF) has been one of the most common neural networks used in the intrusion detection system(IDS). To improve the approximation performance and calculation speed of RBF, we describe a method to deal with the benchmark datasets adopted in the research. It includes converting the string to numeric elements firstly, then omitting the unnecessary data and ensuring that the data has the reasonable range limit. The simulation results built upon Matlab software show that the RBF neural network has better performance than BP neural network.
[1] Jooyoung Park,et al. Universal Approximation Using Radial-Basis-Function Networks , 1991, Neural Computation.
[2] Qiang Chen,et al. Probabilistic techniques for intrusion detection based on computer audit data , 2001, IEEE Trans. Syst. Man Cybern. Part A.
[3] Morteza Amini,et al. RT-UNNID: A practical solution to real-time network-based intrusion detection using unsupervised neural networks , 2006, Comput. Secur..