The application designs a sensitive
data prediction method based on user editing track in a
collaborative editing scene, relates to the field of
data security, and comprises the following steps: obtaining user historical text data, screening
target text containing sensitive data, performing theme division, word segmentation, extracting keywords and position information to establish a
text editing track; for each keyword of the text keyword set, a
context window mechanism is adopted to select a sensitive word set and divide the sensitive word
security level; according to the keyword editing clue, the theme
label and the sensitive word set with the level division, a graph
attention network is used to construct a user track model based on keywords; inputting the editing process text, identifying the keywords and labels, combining the received person role identity level, and inputting the track
graph model to obtain a predicted sensitive word set. The application creates a model based on the user editing track, can accelerate the identification efficiency of sensitive data, reduce the risk of leakage, and improve the sensitive
word identification accuracy under different text themes.