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A New NFT Model to Enhance Copyright Traceability of the Off-chain Data | IEEE Conference Publication | IEEE Xplore

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


Abstract:

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 provision...Show More

Abstract:

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.
Date of Conference: 18-21 August 2022
Date Added to IEEE Xplore: 28 September 2022
ISBN Information:
Conference Location: Lanzhou, China

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