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A Lightweight NFT Auction Protocol for Cross-chain Environment

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Machine Learning for Cyber Security (ML4CS 2022)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13655))

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Abstract

The NFT market has been booming in recent years. In 2021, digital artist Pak’s newest creation, The Merge, fetched US$91.8 million on Nifty Gateway. Since then, many NFT owners have turned to auctions to gain more profits through their collections. Ethereum covers the majority of NFT transactions at the moment. However, it will be hard for them to make profits if they have only one way to sell. To settle this situation, we propose an auction protocol for NFTs which works in a cross-chain environment. We design our protocol by using hash time lock and adding strategies to control users’ malicious behaviors. We also optimize the cross-chain asset exchange process to ensure both auction and exchange are successful. Through testing in Ethereum and FISCO BCOS networks, the experimental results show that our scheme is capable of completing auctions in heterogeneous blockchain networks and maintaining low communication costs. The transactions can be confirmed in an average of 4 blocks, and the contract strategies will filter out invalid transactions. We also do additional experiments to prove that our protocol can resist reentrancy.

This work was supported in part by the Hainan Provincial Natural Science Foundation of China (621RC508), Henan Key Laboratory of Network Cryptography Technology (LNCT2021-A16), the Science Project of Hainan University (KYQD(ZR)-21075).

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Acknowledgements

This work was supported in part by the Hainan Provincial Natural Science Foundation of China (621RC508), Henan Key Laboratory of Network Cryptography Technology (LNCT2021-A16), the Science Project of Hainan University (KYQD(ZR)-21075).

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Correspondence to Wei Ou .

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Guo, H., Chen, M., Ou, W. (2023). A Lightweight NFT Auction Protocol for Cross-chain Environment. In: Xu, Y., Yan, H., Teng, H., Cai, J., Li, J. (eds) Machine Learning for Cyber Security. ML4CS 2022. Lecture Notes in Computer Science, vol 13655. Springer, Cham. https://doi.org/10.1007/978-3-031-20096-0_11

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  • DOI: https://doi.org/10.1007/978-3-031-20096-0_11

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