Athlete Health Data Management from the Perspective of Biotechnology Privacy Protection

Zeng Xiaofang
College of Medicine, Jingchu University of Technology, Jingmen 448000, China
Zhou Ping
College of Medicine, Jingchu University of Technology, Jingmen 448000, China

DOI:https://doi.org/10.5912/jcb2482

Abstract:

In response to the challenges of biological data sensitivity and privacy vulnerabilities in traditional athlete health management systems, this paper proposes a biotechnology-enhanced privacy protection framework integrating federated learning with bio-encryption mechanisms. The methodology systematically categorizes athlete data into temporal biometric patterns, genomic-proteomic biomarkers, sport-specific physiological signatures, and environmental biosensors data. We implement a dual-layer security architecture combining transport layer security with DNA-inspired cryptographic algorithms for secure data transmission. The local model employs a bio-inspired lightweight decision tree optimized for processing biological time-series data, while global aggregation utilizes dynamic weighted learning with biomarker-driven attention mechanisms. To address unique risks in biological data exposure, we develop a hybrid privacy preservation strategy integrating homomorphic encryption for genomic data processing and adaptive Gaussian noise injection calibrated with biological variation coefficients.