Application and Effect Evaluation of Differential Privacy in Genomic Data Medical Services

Genomic data is increasingly widely used in the medical service field, bringing new opportunities for medical development. However, the issue of privacy protection has become prominent, hindering further applications. Differential privacy technology provides a new idea to solve this problem, as it can maintain data availability while ensuring privacy. This article analyzes the threats of genomic data privacy leakage, covering sequencing storage, research analysis, and clinical medical service processes. It elaborates on the differential privacy method, including its formal definition, indistinguishability and other characteristics, and evaluates the application effect in combination with research cases such as pharmacogenomics and personalized medicine. Currently, in practical applications, there are still challenges such as balancing privacy and data utility, technology scalability, and privacy budget setting. In the future, this technology will develop in the direction of integration and innovation with other technologies, expanding application scenarios, and realizing standardization and normalization, and is expected to provide stronger privacy protection support for precision medicine.