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

Research output: Chapters, Conference Papers, Creative and Literary WorksRGC 32 - Refereed conference paper (with host publication)peer-review

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 multidimensional 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. © 2024 IEEE.

Original languageEnglish
Title of host publicationProceedings - 2024 IEEE 35th International Conference on Application-Specific Systems, Architectures and Processors
Subtitle of host publicationASAP 2024
PublisherIEEE
Pages135-142
Number of pages8
ISBN (Electronic)979-8-3503-4963-4
ISBN (Print)979-8-3503-4964-1
DOIs
Publication statusPublished - 2024
Event35th IEEE International Conference on Application-Specific Systems, Architectures and Processors (ASAP 2024) - Charles K. Kao Auditorium, Hong Kong, China
Duration: 24 Jul 202426 Jul 2024
https://www.asap2024.org/

Publication series

NameProceedings of the International Conference on Application-Specific Systems, Architectures and Processors
ISSN (Print)2160-0511
ISSN (Electronic)2160-052X

Conference

Conference35th IEEE International Conference on Application-Specific Systems, Architectures and Processors (ASAP 2024)
PlaceHong Kong, China
Period24/07/2426/07/24
Internet address

Bibliographical note

Publisher Copyright:
© 2024 IEEE.

Funding

This work is supported by Hong Kong Innovation and Technology Commission (InnoHK Project CIMDA), Hong Kong Research Grants Council (Project 11204821), and City University of Hong Kong (Project 9610460).

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 9 - Industry, Innovation, and Infrastructure
    SDG 9 Industry, Innovation, and Infrastructure

Research Keywords

  • AI security
  • AI-generated content
  • blockchain
  • copyright protection
  • low-power AI
  • nanofabrication
  • singular value decomposition (SVD)
  • cs.DC
  • cs.CV

RGC Funding Information

  • RGC-funded

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