The Dark Side of NFTs: A Large-Scale Empirical Study of Wash Trading

被引:0
|
作者
Chen, Shijian [1 ]
Chen, Jiachi [1 ,2 ]
Yu, Jiangshan [3 ]
Luo, Xiapu [4 ]
Wang, Yanlin [1 ]
机构
[1] Sun Yat Sen Univ, Zhuhai, Peoples R China
[2] Zhejiang Univ, State Key Lab Blockchain & Data Secur, Zhuhai, Peoples R China
[3] Univ Sydney, Sydney, NSW, Australia
[4] Hong Kong Polytech Univ, Hong Kong, Peoples R China
基金
中国国家自然科学基金;
关键词
Blockchain; Ethereum; Non-Fungible Tokens; Wash Trading;
D O I
10.1145/3671016.3674808
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
NFTs (Non-Fungible Tokens) have seen significant growth since they first captured public attention in 2021. However, the NFT market is plagued by fake transactions and economic bubbles, e.g., NFT wash trading. Wash trading typically refers to a transaction involving the same person or two colluding individuals, and has become a major threat to the NFT ecosystem. Previous studies only detect NFT wash trading from the financial aspect, while the real-world wash trading cases are much more complicated (e.g., not aiming at inflating the market value). There is still a lack of multi-dimension analysis to better understand NFT wash trading. Therefore, we present the most comprehensive study of NFT wash trading, analyzing 8,717,031 transfer events and 3,830,141 sale events from 2,701,883 NFTs. We identify three types of NFT wash trading and propose identification algorithms. Our experimental results reveal 824 transfer events and 5,330 sale events (accounting for a total of $8,857,070.41) and 370 address pairs related to NFT wash trading behaviors, causing a minimum loss of $3,965,247.13. Furthermore, we provide insights from six aspects, i.e., marketplace design, profitability, NFT project design, payment token, user behavior, and NFT ecosystem.
引用
收藏
页码:447 / 456
页数:10
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