Transferable Unique Copyright Across AI Model Trading: A Blockchain-Driven Non-Fungible Token Approach

Yixin Fan, Guozhi Hao, Jun Wu*

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)

Abstract

Currently, Machine Learning as a Service (MLaaS) greatly benefits artificial intelligence (AI) model trading. However, threats such as model piracy and patent grabbing devastatingly violate the copyright of AI models. Current invasive copyright protection solutions mainly rely on watermarking to embed specific information into AI models, which inevitably decreases the accuracy. While non-invasive schemes, such as adversarial samples, cannot guarantee uniqueness as the adversarial sample generation algorithm would be known to all traders, and thus need to be changed after trading. To enable the ownership information transferable across AI model trading, we propose a blockchain-driven Non-Fungible Token (NFT) approach for trading-oriented AI model copyright protection. We design a mapping mechanism from AI models parameters to NFTs which can identify uniqueness and ownership of AI models across trading. Besides, a reputation-based rewards and penalties scheme is proposed to prevent NFT piracy. Lastly, the evaluation verifies the applicability of our approach.

Original languageEnglish
Title of host publicationProceedings - 2022 IEEE 22nd International Conference on Software Quality, Reliability and Security Companion, QRS-C 2022
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages102-105
Number of pages4
ISBN (Electronic)9798350319910
DOIs
Publication statusPublished - 2022
Event22nd IEEE International Conference on Software Quality, Reliability and Security Companion, QRS-C 2022 - Virtual, Online, China
Duration: 2022 Dec 52022 Dec 9

Publication series

NameProceedings - 2022 IEEE 22nd International Conference on Software Quality, Reliability and Security Companion, QRS-C 2022

Conference

Conference22nd IEEE International Conference on Software Quality, Reliability and Security Companion, QRS-C 2022
Country/TerritoryChina
CityVirtual, Online
Period22/12/522/12/9

Keywords

  • AI model trading
  • Blockchain
  • NFT
  • copyright protection

ASJC Scopus subject areas

  • Software
  • Information Systems and Management
  • Safety, Risk, Reliability and Quality
  • Modelling and Simulation

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