Understanding the dynamic and microscopic traits of typical Ethereum accounts

Abstract

As the most ecologically active cryptocurrency platform, Ethereum has attracted the attention of many researchers. Leveraging its fully public transaction data, most existing analysis models all account interactions as a network and explores it from a static and global perspective. However, their work ignored the investigation of dynamic and microscopic features of accounts. Therefore, we conduct the first work about these features of different kinds of accounts on Ethereum. We select six account types on Ethereum, including exchanges, phishing, etc. Then we characterize and compare the dynamics of their transactions. Next, we construct a transaction ego network for each account, and investigate the network features from the perspective of microscopic structure. Experimental results show that different kinds of accounts have their own traits in terms of transaction features and properties of ego networks, which greatly contributes to understanding their roles. Additionally, there are obvious differences between normal accounts and illegal accounts in some characteristics such as transaction neighbors and interaction patterns. Moreover, we observe that criminal gangs may be participating in phishing scams. Finally, based on the conclusions of the account analysis, we design a variety of account features and use them for the account classification task. The experimental results prove that the dynamic and microscopic features we proposed are beneficial to distinguish different types of accounts. We believe our research can provide reference value for account classification tasks in Ethereum and other blockchains.