TY - GEN
T1 - Tracking Counterfeit Cryptocurrency End-to-end
AU - Gao, Bingyu
AU - Wang, Haoyu
AU - Xia, Pengcheng
AU - Wu, Siwei
AU - Zhou, Yajin
AU - Luo, Xiapu
AU - Tyson, Gareth
N1 - Funding Information:
The full paper appears at [1]. This work was supported by the National Natural Science Foundation of China (grants No.61702045 and No.62072046), Hong Kong RGC Project (No. 152193/19E), the Fundamental Research Funds for the Central Universities, Leading Innovative and Entrepreneur Team Introduction Program of Zhe-jiang (2018R01005). Haoyu Wang ([email protected]) is the corresponding author.
Publisher Copyright:
© 2021 Owner/Author.
PY - 2021/5/31
Y1 - 2021/5/31
N2 - With the growth of the cryptocurrency ecosystem, there is expanding evidence that counterfeit cryptocurrency has also appeared. In this paper, we empirically explore the presence of counterfeit cryptocurrencies on Ethereum and measure their impact. By analyzing over 190K ERC-20 tokens (or cryptocurrencies) on Ethereum, we have identified 2,117 counterfeit tokens that target 94 of the 100 most popular cryptocurrencies. We perform an end-to-end characterization of the counterfeit token ecosystem, including their popularity, creators and holders, fraudulent behaviors and advertising channels. Through this, we have identified two types of scams related to counterfeit tokens and devised techniques to identify such scams. We observe that over 7,104 victims were deceived in these scams, and the overall financial loss sums to a minimum of $17 million (74,271.7 ETH). Our findings demonstrate the urgency to identify counterfeit cryptocurrencies and mitigate this threat.
AB - With the growth of the cryptocurrency ecosystem, there is expanding evidence that counterfeit cryptocurrency has also appeared. In this paper, we empirically explore the presence of counterfeit cryptocurrencies on Ethereum and measure their impact. By analyzing over 190K ERC-20 tokens (or cryptocurrencies) on Ethereum, we have identified 2,117 counterfeit tokens that target 94 of the 100 most popular cryptocurrencies. We perform an end-to-end characterization of the counterfeit token ecosystem, including their popularity, creators and holders, fraudulent behaviors and advertising channels. Through this, we have identified two types of scams related to counterfeit tokens and devised techniques to identify such scams. We observe that over 7,104 victims were deceived in these scams, and the overall financial loss sums to a minimum of $17 million (74,271.7 ETH). Our findings demonstrate the urgency to identify counterfeit cryptocurrencies and mitigate this threat.
KW - blockchain
KW - counterfeit cryptocurrency
KW - ethereum
KW - scam
UR - http://www.scopus.com/inward/record.url?scp=85108559115&partnerID=8YFLogxK
U2 - 10.1145/3410220.3456282
DO - 10.1145/3410220.3456282
M3 - Conference article published in proceeding or book
AN - SCOPUS:85108559115
T3 - SIGMETRICS 2021 - Abstract Proceedings of the 2021 ACM SIGMETRICS / International Conference on Measurement and Modeling of Computer Systems
SP - 33
EP - 34
BT - SIGMETRICS 2021 - Abstract Proceedings of the 2021 ACM SIGMETRICS / International Conference on Measurement and Modeling of Computer Systems
PB - Association for Computing Machinery, Inc
T2 - 2021 ACM SIGMETRICS / International Conference on Measurement and Modeling of Computer Systems, SIGMETRICS 2021
Y2 - 14 June 2021 through 18 June 2021
ER -