Research on a dynamic data security risk assessment method based on behavioral pattern recognition

In order to solve the problem that traditional risk assessment methods can not accurately assess data security risks, a dynamic assessment method of data security risks based on behavior pattern recognition is proposed. In this paper, the main body of the evaluation model is constructed by optimizing the technical path of neural network and behavior pattern recognition, then the selection criteria of evaluation indicators are established, the evaluation data is preprocessed, and finally the evaluation model is trained. The experimental results show that the average classification accuracy of the evaluation method designed in this paper and the traditional evaluation method is 85% and 75% respectively, and the running time is 4.5s and 5.0s respectively. Conclusion: This method can enhance the accuracy of safety risk assessment.