Research on Secure Communication Model for Station Based on Multi-Factor Identity Authentication

With the advancement of communication technology, the diversity and number of terminal devices in the station communication network continue to grow, and the traditional single authentication method has been difficult to meet the needs of modern complex network environments, especially in critical areas such as smart grids. Unauthorized access and identity impersonation have gradually become the primary security problems faced by these domains. In response to this problem, this paper provides an in-depth discussion of the multi-factor identity authentication technique that fuses passwords, certificates, trustworthy hardware and other identity authentication factors, and constructs an identity authentication scheme based on decision-level fusion. To further enhance the accuracy and efficiency of identification, we have also incorporated deep learning techniques that enable the model to automatically learn and extract key features. The experimental results show that the station secure communication model based on multi-factor identity authentication can effectively improve the security of terminal devices in the station communication network while providing authentication accuracy.