Network Security State Evaluation Based on BP Network Improved Fuzzy Evaluation Membership Function

The article presents a method for evaluating network security state using an improved fuzzy evaluation membership function and BP neural networks. The method involves constructing a BP neural network model based on network security behavior data and introducing an enhanced fuzzy evaluation membership function that more accurately describes the relationship between network behavior features and security states. Through training and adjusting the model, the method enables accurate evaluation and prediction of network security states, effectively identifying and predicting security threats in networks. Experimental results demonstrate that the method has high accuracy and reliability, making it potentially valuable in the field of network security.