Intrusive Detection Systems Design based on BP Neural Network

Objective: An intrusion detection system was constructed on the basis of the characteristics of BP neural network model. Methods: According to the capture engine of the text, all network data stream flowed through the systematic monitoring network segment will be captured, feature extraction module analyze and process the captured network data flow, you can extract complete and accurate eigenvector on behalf of this data stream, and this eigenvector will be presented to the neural network classification engine, as the input vector of a neural network Results: The neural network classification engine analyzes and processes this eigenvector, and thus distinguishes whether it is the intrusive action.