Characterizing Transfer Graphs of Suspicious ERC-20 Tokens

Fuente: arXiv
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Hauptverfasser: Josenhans, Calvin, Kuehlkamp, Andrey, Nabrzyski, Jarek
Format: Preprint
Veröffentlicht: 2025
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author Josenhans, Calvin
Kuehlkamp, Andrey
Nabrzyski, Jarek
author_facet Josenhans, Calvin
Kuehlkamp, Andrey
Nabrzyski, Jarek
contents Ethereum is currently the second largest blockchain by market capitalization and a popular platform for cryptocurrencies. As it has grown, the high value present and the anonymity afforded by the technology have led Ethereum to become a hotbed for various cybercrimes. This paper seeks to understand how these fraudulent schemes may be characterized and develop methods for detecting them. One key feature introduced by Ethereum is the ability to use programmable smart contracts to execute code on the blockchain. A common use of smart contracts is implementing fungible tokens with the ERC-20 interface. Such tokens can be used to impersonate legitimate tokens and defraud users. By parsing the event logs emitted by these ERC-20 contracts over 20 different periods of 100K blocks, we construct token transfer graphs for each of the available ERC-20 tokens on the blockchain. By analyzing these graphs, we find a set of characteristics by which suspicious contracts are distinguished from legitimate ones. These observations result in a simple model that can identify scam contracts with an average of 88.7% accuracy. This suggests that the mechanism by which fraudulent schemes function strongly correlates with their transfer graphs and that these graphs may be used to improve scam-detection mechanisms, contributing to making Ethereum safer.
format Preprint
id arxiv_https___arxiv_org_abs_2501_11668
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Characterizing Transfer Graphs of Suspicious ERC-20 Tokens
Josenhans, Calvin
Kuehlkamp, Andrey
Nabrzyski, Jarek
Cryptography and Security
Ethereum is currently the second largest blockchain by market capitalization and a popular platform for cryptocurrencies. As it has grown, the high value present and the anonymity afforded by the technology have led Ethereum to become a hotbed for various cybercrimes. This paper seeks to understand how these fraudulent schemes may be characterized and develop methods for detecting them. One key feature introduced by Ethereum is the ability to use programmable smart contracts to execute code on the blockchain. A common use of smart contracts is implementing fungible tokens with the ERC-20 interface. Such tokens can be used to impersonate legitimate tokens and defraud users. By parsing the event logs emitted by these ERC-20 contracts over 20 different periods of 100K blocks, we construct token transfer graphs for each of the available ERC-20 tokens on the blockchain. By analyzing these graphs, we find a set of characteristics by which suspicious contracts are distinguished from legitimate ones. These observations result in a simple model that can identify scam contracts with an average of 88.7% accuracy. This suggests that the mechanism by which fraudulent schemes function strongly correlates with their transfer graphs and that these graphs may be used to improve scam-detection mechanisms, contributing to making Ethereum safer.
title Characterizing Transfer Graphs of Suspicious ERC-20 Tokens
topic Cryptography and Security
url https://arxiv.org/abs/2501.11668