Characterizing Transfer Graphs of Suspicious ERC-20 Tokens
Calvin Josenhans, Andrey Kuehlkamp, Jarek Nabrzyski

TL;DR
This paper analyzes transfer graphs of ERC-20 tokens on Ethereum to identify characteristics of scam contracts, developing a model that detects fraudulent schemes with high accuracy, thereby enhancing blockchain security.
Contribution
It introduces a novel graph-based analysis of ERC-20 token transfers to distinguish suspicious contracts from legitimate ones, improving scam detection methods.
Findings
Suspicious contracts exhibit distinct transfer graph characteristics.
The proposed model achieves 88.7% average accuracy in identifying scam contracts.
Transfer graph analysis can significantly enhance Ethereum scam detection.
Abstract
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…
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Taxonomy
TopicsInterconnection Networks and Systems · Advanced Graph Theory Research · Complexity and Algorithms in Graphs
