A Neural Network Based Intrusion Detection Data Fusion Model

摘要

The abilities of summarization, learning and selffitting and inner-parallel computing make artificial neural networks suitable for intrusion detection. On the other hand, data fusion based IDS has been used to solve the problem of distorting rate and failingto-report rate and improve its performance. However, Multi-sensor input-data makes the IDS lose its efficiency. The research of neural network based data fusion IDS tries to combine the strong process ability of neural network with the advantages of data fusion IDS. A neural network is designed to realize the data fusion and intrusion analysis and pruning algorithm of neural networks is used for filtering information from multi-sensors.