With the development of market economy, the manufacturing industry is facing more and more competition and risks. In order to comply with the trend of the network, this paper draws lessons from the idea of the Information Centric‐Networking, and regards the content as the most important support for the development of the manufacturing industry. Therefore, it is necessary to evaluate and consider the risk and security of the manufacturing data, and provide safeguard measures. In the traditional information security prediction methods, the accuracy of data is required, but there are too many uncertain factors in the prediction process, so the accuracy will be greatly reduced by using traditional methods. In order to ensure the accuracy of security risk prediction in manufacturing enterprises, this paper proposes a prediction method that combines fuzzy theory with Back Propagation (BP) neural network. In this method, the fuzzy theory is used to preprocess the data, and the preprocessed data is used as the input of the neural network, then the BP neural network is used for training and testing, and finally the level of enterprise information security risk is obtained. The simulation results show that this method can achieve high accuracy, and its accuracy is higher than that of the traditional method.