Design and Optimization of Privacy Protection Algorithms in Hospital Information Systems

This study aims to enhance privacy protection algorithms in hospital information systems by proposing a differential privacy approach to secure patients' sensitive data. The study initially looked into the necessity for privacy protections in hospital information systems, stressing the significance of balancing privacy and data usefulness when handling medical information. The differential privacy mechanism was implemented to address privacy leakage risks during data anonymization, leading to enhanced data processing efficiency. The experimental design used a simulated hospital information system data set to analyze and verify the performance of the proposed algorithm, proving its effectiveness under different privacy parameter settings. The experimental results show that the algorithm can achieve a good balance between data practicality and privacy protection, and improve computational efficiency, which is suitable for large-scale medical data processing. The research also investigated how various privacy settings affect algorithm efficiency, offering valuable insight for implementing hospital information systems. The study's successful execution established the groundwork for using privacy protection algorithms in the medical sector, and introduced a privacy protection technique that can serve as a model for other industries with sensitive data.