Research on Multi-layer Adaptive Intrusion Detection Based on Clustering and Neural Network

Aiming at the shortcomings of current intrusion detection, a SOM neural network method based on clustering and network level is proposed in this paper. Through the identification of easy-to-use network intrusion type, the network intrusion data is cleaned and analyzed in a targeted manner and the multi-layer adaptive network intrusion detection clustering model is established. Network intrusion detection clustering result based on this model is compared with result based on other methods. The results show that this model has higher accuracy and equilibrium and the validity and feasibility of the method is further verified.