# Blockchain-Empowered Lifecycle Management for AI-Generated Content (AIGC) Products in Edge Networks

arXiv: https://arxiv.org/abs/2303.02836 · HTML: https://mlsanity.com/paper/2303.02836/

## Key facts

- Cited by 6 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 6 Mar 2023.

## Built on by (most cited first, 6 of 6)

- [Enhancing Deep Reinforcement Learning: A Tutorial on Generative Diffusion Models in Network Optimization](https://mlsanity.com/paper/2308.05384/) (2023)
- [Deep Generative Model and Its Applications in Efficient Wireless Network Management: A Tutorial and Case Study](https://mlsanity.com/paper/2303.17114/) (2023)
- [Challenges and Remedies to Privacy and Security in AIGC: Exploring the Potential of Privacy Computing, Blockchain, and Beyond](https://mlsanity.com/paper/2306.00419/) (2023)
- [Who Owns the Output? Bridging Law and Technology in LLMs Attribution](https://mlsanity.com/paper/2504.01032/) (2025)
- [A Survey of Blockchain, Artificial Intelligence, and Edge Computing for Web 3.0](https://mlsanity.com/paper/2311.13731/) (2023)
- [Copyleft for Alleviating AIGC Copyright Dilemma: What-if Analysis, Public Perception and Implications](https://mlsanity.com/paper/2402.12216/) (2024)

## Abstract (arXiv)

The rapid development of Artificial IntelligenceGenerated Content (AIGC) has brought daunting challenges regarding service latency, security, and trustworthiness. Recently, researchers presented the edge AIGC paradigm, effectively optimize the service latency by distributing AIGC services to edge devices. However, AIGC products are still unprotected and vulnerable to tampering and plagiarization. Moreover, as a kind of online non-fungible digital property, the free circulation of AIGC products is hindered by the lack of trustworthiness in open networks. In this article, for the first time, we present a blockchain-empowered framework to manage the lifecycle of edge AIGC products. Specifically, leveraging fraud proof, we first propose a protocol to protect the ownership and copyright of AIGC, called Proof-of-AIGC. Then, we design an incentive mechanism to guarantee the legitimate and timely executions of the funds-AIGC ownership exchanges among anonymous users. Furthermore, we build a multi-weight subjective logic-based reputation scheme, with which AIGC producers can determine which edge service provider is trustworthy and reliable to handle their services. Through numerical results, the superiority of the proposed approach is demonstrated. Last but not least, we discuss important open directions for further research.