A Method of Detecting Sensitive Information of Enterprise Asset Training Education Based on Machine Learning

Enterprises inevitably involve sensitive information when organizing asset training and education activities. To ensure information security, a machine learning based method for detecting sensitive information in enterprise asset training and education has been proposed. First, preprocess the enterprise asset training and education information text by word segmentation and removing Stop word. Then, the Bayesian network in machine learning is used to extract the characteristic words of the sensitive information of enterprise asset training and education, and then the enterprise asset training and education is expressed through the Vector space model. Finally, using the k-means clustering algorithm in machine learning, a sensitive information detection model is constructed to achieve sensitive information detection in enterprise asset training education. The experimental results indicate that the accuracy and recall of the studied method are higher, and the F-Measure is larger, which proves the effectiveness of the sensitive information detection method studied.