RO-SVD: A Reconfigurable Hardware Copyright Protection Framework for AIGC Applications
This addresses copyright issues for users and developers of AI-generated content, but it is incremental as it applies existing methods like blockchain and SVD to a new domain.
The paper tackles the problem of copyright protection for AI-generated content by proposing a blockchain-based framework called RO-SVD that uses hardware entropy and decomposition computing to establish device-level traceability, demonstrating effectiveness with AI-generated images and offering a low-cost solution.
The dramatic surge in the utilisation of generative artificial intelligence (GenAI) underscores the need for a secure and efficient mechanism to responsibly manage, use and disseminate multi-dimensional data generated by artificial intelligence (AI). In this paper, we propose a blockchain-based copyright traceability framework called ring oscillator-singular value decomposition (RO-SVD), which introduces decomposition computing to approximate low-rank matrices generated from hardware entropy sources and establishes an AI-generated content (AIGC) copyright traceability mechanism at the device level. By leveraging the parallelism and reconfigurability of field-programmable gate arrays (FPGAs), our framework can be easily constructed on existing AI-accelerated devices and provide a low-cost solution to emerging copyright issues of AIGC. We developed a hardware-software (HW/SW) co-design prototype based on comprehensive analysis and on-board experiments with multiple AI-applicable FPGAs. Using AI-generated images as a case study, our framework demonstrated effectiveness and emphasised customisation, unpredictability, efficiency, management and reconfigurability. To the best of our knowledge, this is the first practical hardware study discussing and implementing copyright traceability specifically for AI-generated content.