AIGC-Chain: A Blockchain-Enabled Full Lifecycle Recording System for AIGC Product Copyright Management

2024-06-21

arXiv.org

AI Summary

To address the ambiguity in copyright ownership of AI-generated content (AIGC) arising from its lack of human originality and the inadequacy of existing legal frameworks for rights attribution, this paper proposes a blockchain-based, full-lifecycle copyright notarization system. The method introduces a novel lightweight copyright provenance mechanism integrating Istanbul Byzantine Fault Tolerance (IBFT), enabling fine-grained on-chain recording of prompt inputs, model invocations, content generation, and downstream distribution—while establishing explicit mappings between on-chain behavioral records and legal rights holders. Leveraging an Ethereum-compatible architecture, hash anchoring, and multi-source metadata notarization, the system ensures immutability while reducing on-chain storage overhead by 62% and supporting millisecond-scale provenance queries. In simulated auditing experiments, it achieves 100% detection accuracy for forged copyright claims, thereby delivering a verifiable, efficient, and regulation-compliant technical infrastructure for AIGC copyright assertion.

Technology Category

• Philosophy and Ethics of AI: Artificial General Intelligence
• Multiagent Systems: Mechanism Design
• Humans and AI: Game Design — Procedural Content Generation & Storytelling

Application Category

• Economics, Online Markets and Human Computation: Economic ramifications for generative AI infrastructure and applications
• Social Networks and Social Media: Generative AI / large language models and their impact on social systems
• Search and Retrieval-Augmented AI: Agentic search

Abstract

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.

Problem

• Addresses copyright ownership challenges in AI-generated content (AIGC).
• Proposes blockchain-based lifecycle recording for AIGC copyright management.
• Ensures secure multi-party supervision to resolve AIGC copyright disputes.

Innovation

• Full lifecycle recording of AIGC data
• Decentralized blockchain for secure supervision
• Multi-party auditing for copyright dispute resolution