Strategies for the source protection of data assets on processing techniques for intelligent manufacturing in traditional Chinese medicine.

The digital transformation of traditional Chinese medicine (TCM) processing techniques currently faces a critical industry bottleneck: the lack of rights protection for source knowledge contributors, which results in an insufficient supply of high-quality data. Applying principles from information economics and algorithmic theory, this study analyzes risk mechanisms where physical control fails during technical externalization and institutional safeguards are undermined by algorithmic "black box" complexity. To address these vulnerabilities, a full-cycle safeguarding system was established through a synergy of institutional and technological measures. This analysis suggests that institutional data intellectual property registration may clarify ownership and facilitate benefit-sharing, while technological implementations - specifically transformation-domain digital watermarking and model backdoor detection - offer a promising pathway toward robust data traceability. This integrated strategy has the potential to address the challenges of safeguarding contributor rights and could activate the endogenous motivation for data supply. Consequently, this framework may provide a foundation for fostering new productive forces and supporting the sustainable, high-quality development of the intelligent TCM manufacturing industry.