An Identity Management Scheme Based on Multi-Factor Authentication and Dynamic Trust Evaluation for Telemedicine

Telemedicine diagnosis has become a more flexible and convenient way to receive diagnoses, which is of great significance in enhancing diagnosis, cutting costs, and serving remote users. However, telemedicine faces many security problems, such as the complexity of user authentication, the balance of the existing biometric factor authentication scheme, the unpredictability of user behavior, and the difficulty of unified authentication due to the differences in the security standards and authentication mechanisms of different trust domains, which affect the sustainable development of telemedicine. To address the above issues, this paper presents an identity management scheme based on multi-factor authentication and dynamic trust evaluation for telemedicine. Its authentication combines iris recognition for secure biometric verification, smart cards for encrypted credential storage, and static passwords for supplementary verification, addressing scenarios like facial coverage in medical settings. The scheme dynamically adjusts authentication based on attack rates, login anomalies, and service durations. By integrating ShangMi cryptographic algorithms and blockchain, it optimizes performance, achieving 35% lower communication overhead than previous protocols. A security analysis shows it resists impersonation, man-in-the-middle, and password modification attacks while preserving user anonymity. System evaluation meets authoritative standards, validating its practicality. This scheme balances security and efficiency, providing a strong basis for telemedicine's long-term viability.