RO-SVD: A Reconfigurable Hardware Copyright Protection Framework for AIGC Applications

TL;DR

This paper introduces RO-SVD, a reconfigurable FPGA-based framework that ensures secure copyright traceability for AI-generated content using blockchain and low-rank matrix approximation techniques.

Contribution

It presents the first practical hardware implementation of a copyright traceability system specifically designed for AI-generated content using RO-SVD and FPGA technology.

Findings

Effective copyright traceability demonstrated with AI-generated images

Framework offers customization, unpredictability, and reconfigurability

Low-cost, hardware-software co-design prototype validated on multiple FPGAs

Abstract

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.