TY - GEN
T1 - The Dark Side of NFTs: A Large-Scale Empirical Study of Wash Trading
AU - Chen, Shijian
AU - Chen, Jiachi
AU - Yu, Jiangshan
AU - Luo, Xiapu
AU - Wang, Yanlin
N1 - Publisher Copyright:
© 2024 ACM.
PY - 2024/7/24
Y1 - 2024/7/24
N2 - 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.
AB - 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.
KW - Blockchain
KW - Ethereum
KW - Non-Fungible Tokens
KW - Wash Trading
UR - http://www.scopus.com/inward/record.url?scp=85200847280&partnerID=8YFLogxK
U2 - 10.1145/3671016.3674808
DO - 10.1145/3671016.3674808
M3 - Conference article published in proceeding or book
AN - SCOPUS:85200847280
T3 - ACM International Conference Proceeding Series
SP - 447
EP - 456
BT - 15th Asia-Pacific Symposium on Internetware, Internetware 2024 - Proceedings
PB - Association for Computing Machinery
T2 - 15th Asia-Pacific Symposium on Internetware, Internetware 2024
Y2 - 24 July 2024 through 26 July 2024
ER -