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<scp>TokenScout:</scp> Early Detection of Ethereum Scam Tokens via Temporal Graph Learning

Cong Wu, Jing Chen, Ziming Zhao, Kun He, Guowen Xu, Yueming Wu, Haijun Wang, Hongwei Li, Yang Liu, Yang Xiang

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Abstract

Decentralized finance has experienced phenomenal growth, revolutionizing the landscape of financial transactions and asset management via blockchain. Yet, this swift growth brings with it substantial challenges, notably the surge in scam tokens, imposing significant security threats on cryptocurrency investments and trading. Existing detection methods of scam token, primarily relying on analyzing contract codes or transaction patterns, struggle to catch increasingly sophisticated tactics employed by scammers. For example, contract-based analysis are unable to identify scams lacking overt malicious code, e.g., most rugpulls, while transaction-based methods generally lack the foresight to early-detect potential risks.

Topics & Concepts

Security tokenCryptocurrencyDatabase transactionComputer scienceBlockchainComputer securityCode (set theory)Futures studiesFinancial transactionArtificial intelligenceDatabaseSet (abstract data type)Programming languageBlockchain Technology Applications and SecurityCrime, Illicit Activities, and GovernanceSpam and Phishing Detection
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