Heterogeneous Network Representation Learning Approach for Ethereum Identity Identification

【Author】 Wang, Yixian; Liu, Zhaowei; Xu, Jindong; Yan, Weiqing

【Source】IEEE TRANSACTIONS ON COMPUTATIONAL SOCIAL SYSTEMS

【影响因子】4.747

【Abstract】Recently, network representation learning has been widely used to mine and analyze network characteristics, and it is also applied to blockchain, but most of the embedding methods in blockchain ignore the heterogeneity of network, so it is difficult to accurately describe the characteristics of the transaction. As smart society evolves, Ethereum makes smart contracts reality, while the mine of transaction characteristics appearing on the Ethereum platform is scarce; thus, there is an urgent need to mine Ethereum from contract and transfer. In this article, we propose a heterogeneous network representation learning method to mine implicit information inside Ethereum transactions. Specifically, we construct an Ethereum transaction network by collecting transaction data from normal and phishing Ethereum accounts. Then, we propose a walk strategy that combines timestamps and transaction amounts to represent the information that occurs at the time of a transaction. To mine the types of nodes and edges, we use a heterogeneous network representation learning method to map the transaction network to a low-dimensional space. Finally, we improve the accuracy of the embedding results in the node classification task, which has important implications for Ethereum mining as well as identity recognition.

【Keywords】Task analysis; Heterogeneous networks; Smart contracts; Cryptocurrency; Blockchains; Representation learning; Phishing; Ethereum; heterogeneous network representation learning; node classification; transactions network

【发表时间】

【收录时间】2022-07-19

【文献类型】期刊

【主题类别】

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