Deepfake-driven Disinformation Dissemination in Biotechnology: Mechanisms and Governance Strategies

Daiyan Cao
School of Radio and Television, Liaoning University, Shenyang, 110000, Liaoning, China

Abstract:

With the increasing integration of deepfake technology into biomedical and biotechnology domains, the risk of disinformation through falsified genetic data, clinical trial outcomes, and medical imagery has grown significantly. This paper explores the mechanisms by which deepfake content spreads within the biotechnology sector, including via encrypted messaging tools, social media platforms, and industry-specific databases. Furthermore, we propose a multi-layered governance strategy leveraging DNA-based biometric features and manifold-based detection systems. By combining AI-driven deepfake detection with biologically grounded authentication techniques such as DNA watermarking and bio-sensor integration, this work outlines a commercial-ready model for safeguarding biotech enterprises against synthetic data threats. The study also discusses ethical and regulatory implications, particularly under emerging data privacy laws applicable to genetic information. This research provides actionable insights into combating deepfake misinformation in high-stakes, data-driven biotech environments.