Big Data-Enhanced Encryption Techniques for Securing Biotechnology Data

Yongfeng Zhang
Center of Energy Development Research, Sichuan University, Chengdu, China, 610065

DOI:https://doi.org/10.5912/jcb1141

Abstract:

This paper introduces an innovative approach to data encryption in the biotechnology sector by integrating big data analytics with intelligent encryption methods, aimed at securing sensitive biotech data. The method is designed to handle large datasets typical in biotechnology, including genomic data, clinical trial data, and deregulated research information. By merging real-time and historical biotech data, our system enhances the security protocols across various stages of biotech data handling, from data acquisition to analysis and reporting. The framework leverages machine learning to enhance data security measures within the biotechnology database systems. Advanced statistical techniques and computational algorithms integrate and encrypt data, protecting against unauthorized access and potential data breaches. Simulation results over a three-year period demonstrate that our intelligent encryption method not only secures data but also optimizes data handling efficiency in biotech environments. Furthermore, the paper discusses the application of this system in biotech e-commerce platforms, where the encryption method supports secure data transactions and improves the effectiveness of marketing strategies. Experimental research and analysis confirm that the proposed system substantially enhances the security and performance of data-driven tasks in biotechnology, providing a robust solution for managing sensitive information in the industry.