A New NFT Model to Enhance Copyright Traceability of the Off-chain Data

Yulong Chen; Ziwei Wang; Xiangyu Liu; Xuetao Wei

10.1109/CoST57098.2022.00041

2022

978-1-6654-6249-5

2022 International Conference on Culture-Oriented Science and Technology (CoST)

157-162

18-21 Aug. 2022

Lanzhou, China

Non-Fungible Tokens (NFTs) are digital assets that represent real-world objects like art, music and videos. However, NFTs according to current standards have no provisions for the copyright traceability of the off-chain data, which greatly hinders the sustainability of the NFT community. In this paper, we propose a new NFT model, which is a synergy of a new economic mechanism backed by game theory and two supplementary algorithms to handle the off-chain data. The economic mechanism is first proposed to motivate participants to maintain the off-chain raw data. Then, the model includes two supplementary algorithms, the version algorithm and validation algorithm, to verify the NFT’s ownership and copyright. We implement our model in Solidity on Ethereum and conduct experiments based on the real-world dataset from the largest NFT marketplace OpenSea. Our evaluation demonstrates that our model is a promising attempt towards the copyright traceability of the off-chain data for NFTs.

blockchain NFT model copyright

第一

IEEE

Department of Computer Science and Engineering, Southern University of Science and Technology, Shenzhen, China

Yulong Chen,Ziwei Wang,Xiangyu Liu,et al. A New NFT Model to Enhance Copyright Traceability of the Off-chain Data[C],2022:157-162.