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.