Abstract
Non-fungible tokens (NFTs) are digital representations of assets stored on a blockchain. It allows content creators to certify authenticity of their digital assets and transfer ownership in a transparent and decentralized way. Popular choices of NFT marketplaces infrastructure include blockchains with smart contract functionality or layer-2 solutions. Surprisingly, researchers have largely avoided building NFT schemes over Bitcoin-like blockchains, most likely due to high transaction fees in the BTC network and the belief that Bitcoin lacks enough programmability to implement fair exchanges. In this work we fill this gap. We propose an NFT scheme where trades are settled in a single Bitcoin transaction as opposed to executing complex smart contracts. We use zero-knowledge proofs (concretely, recursive SNARKs) to prove that two Bitcoin transactions, the issuance transaction \(\textsf{tx}_0\) and the current trade transaction \(\textsf{tx}_n\), are linked through a unique chain of transactions. Indeed, these proofs function as “off-chain receipts” of ownership that can be transferred from the current owner to the new owner using an insecure channel. The size of the proof receipt is short, independent of the total current number of trades n, and can be updated incrementally by anyone at anytime. Marketplaces typically require some degree of token ownership delegation, e.g., escrow accounts, to execute the trade between sellers and buyers that are not online concurrently, and to alleviate transaction fees they resort to off-chain trades. This raises concerns on the transparency and purportedly honest behaviour of marketplaces. We achieve fair and non-custodial trades by leveraging our off-chain receipts and letting the involved parties carefully sign the trade transaction with appropriate combinations of \(\texttt {sighash}\) flags.
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Kiraz, M.S., Larraia, E., Vaughan, O. (2023). NFT Trades in Bitcoin with Off-Chain Receipts. In: Zhou, J., et al. Applied Cryptography and Network Security Workshops. ACNS 2023. Lecture Notes in Computer Science, vol 13907. Springer, Cham. https://doi.org/10.1007/978-3-031-41181-6_6
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