Application of Grey Neural Network Forecasting Model Based on Background Value Improvement in Enterprise Network Security Evaluation

Network security is related to the proper protection of the network system hardware, software, and the data in the system. They are not subjected to accidental or malicious destruction, alteration and disclosure to make the system run continuously and reliably. Then, the network service is not interrupted. As we all know, BP neural network is used more fully in the network security. It has a strong nonlinear approximation ability, the algorithm is simple and easy to implement, but it is easy to fall into local extreme value, which is difficult to ensure that the algorithm converges to the global minimum point, and the global search ability is not strong. Based on this, this paper makes an improvement on the background value of grey model, and uses the output value of the gray model to establish the neural network forecasting model. In addition, this paper presents a decision method of the importance degree of the enterprise network security evaluation index which is based on BP neural network. The main feature of this method is that the evaluation index is extracted directly from the network connection weights. Finally, this article proves that the grey neural forecasting model based on background value improvement can be used to evaluate the development trend of enterprise network security more accurately.