As artificial intelligence technology becomes increasingly prevalent, Artificial Intelligence Generated Content (AIGC) is being adopted across various sectors. Although AIGC is playing an increasingly significant role in business and culture, questions surrounding its copyright have sparked widespread debate. The current legal framework for copyright and intellectual property is grounded in the concept of human authorship, but in the creation of AIGC, human creators primarily provide conceptual ideas, with AI independently responsible for the expressive elements. This disconnect creates complexity and difficulty in determining copyright ownership under existing laws. Consequently, it is imperative to reassess the intellectual contributions of all parties involved in the creation of AIGC to ensure a fair allocation of copyright ownership. To address this challenge, we introduce AIGC-Chain, a blockchain-enabled full lifecycle recording system designed to manage the copyright of AIGC products. It is engineered to meticulously document the entire lifecycle of AIGC products, providing a transparent and dependable platform for copyright management. Furthermore, we propose a copyright tracing method based on an Indistinguishable Bloom Filter, named IBFT, which enhances the efficiency of blockchain transaction queries and significantly reduces the risk of fraudulent copyright claims for AIGC products. In this way, auditors can analyze the copyright of AIGC products by reviewing all relevant information retrieved from the blockchain.

翻译：随着人工智能技术的日益普及，人工智能生成内容（AIGC）正被广泛应用于各个领域。尽管AIGC在商业和文化领域扮演着越来越重要的角色，但其版权问题已引发广泛争议。现行的版权与知识产权法律框架建立在人类作者身份概念之上，但在AIGC创作过程中，人类创作者主要提供概念构思，而表达性元素则由AI独立完成。这种脱节导致依据现有法律判定版权归属时产生复杂性与困难。因此，有必要重新评估AIGC创作过程中各参与方的智力贡献，以确保版权归属的公平分配。为应对这一挑战，我们提出了AIGC-Chain——一个基于区块链的全生命周期记录系统，旨在管理AIGC产品的版权。该系统经过精心设计，可详尽记录AIGC产品的完整生命周期，为版权管理提供透明可靠的技术平台。此外，我们提出了一种基于不可区分布隆过滤器的版权追溯方法（命名为IBFT），该方法能提升区块链交易查询效率，并显著降低AIGC产品遭受欺诈性版权主张的风险。通过这种方式，审计人员可通过分析从区块链检索的所有相关信息来核查AIGC产品的版权归属。