Towards Reliable Utilization of AIGC: Blockchain-Empowered Ownership Verification Mechanism
IEEE OPEN JOURNAL OF THE COMPUTER SOCIETY(2023)
Abstract
With the development of the blockchain technology, a decentralized and de-trusted network paradigm has been constructed, enabling multiple digital assets like NFT, to be permanently recorded and authenticated by blockchain. Also, the uniqueness and verifiability of these assets allows them to flow and generate value between any network entities. With the emergence of AI Generative Content (AIGC), the ownership of models and generative contents, which are also digital assets, has not been well protected. Both because the black-box nature of neural networks makes it difficult to mark models' ownership and because the lack of a reliable third-party verification platform. Meanwhile, the existing model-attack threat and raising ethical problems driven the research on model watermark embedding for traceability and verification, and thus the reliable basic algorithm and the verification platform are needed. In this survey, while emphasizing the importance and reason of the ownership protection in AIGC and summarizing the recent research using model watermarking, we will also introduce the achievements of blockchain in copyright in order to summarize the research history and point out future direction of model copyright validation from both the underlying technology and the supporting platform.
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Key words
Blockchains,Training,Data models,Reliability,Federated learning,Training data,Copyright protection,Blockchain,copyright,federated learning,ownership,AIGC
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