Design of a Big Data Sensitive Information Monitoring System Based on Convolutional Neural Networks
Sensitive information management is facing new challenges in the context of big data,The difficulty of effectively monitoring sensitive information is increasing.In response to the characteristics of low classification accuracy,long time consumption,misjudgment,difficulty in tracing and locating sources,and difficulty in obtaining evidence in traditional monitoring and judgment methods,This article investigates the application of convolutional neural network models and naive Bayesian algorithms in the classification,recognition,and monitoring of sensitive information in the context of big data,Adopting the framework of TensorFlow and Keras,using naive Bayesian algorithm for sensitive information classification,and constructing a fast and accurate digital display system for identifying and monitoring sensitive information.The system has the advantages of high classification accuracy,short time consumption,less misjudgment,and traceability.
万方数据
维普
