【Author】
Lin, Dan; Wu, Jiajing; Yuan, Qi; Zheng, Zibin
【Source】IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS II-EXPRESS BRIEFS
【Abstract】As the largest public blockchain-based platform supporting smart contracts, Ethereum has accumulated a large number of user transaction records since its debut in 2014. Analysis of Ethereum transaction records, however, is still relatively unexplored till now. Modeling the transaction records as a static simple graph, existing methods are unable to accurately characterize the temporal and multiplex features of the edges. In this brief, we first model the Ethereum transaction records as a complex network by incorporating time and amount features of the transactions, and then design several flexible temporal walk strategies for random-walk based graph representation of this large-scale network. Experiments of temporal link prediction on real Ethereum data demonstrate that temporal information and multiplicity characteristic of edges are indispensable for accurate modeling and understanding of Ethereum transaction networks.
【Keywords】Complex networks; Data mining; Circuits and systems; Smart contracts; Data models; Blockchain; Social networking (online); Ethereum; blockchain; complex networks; graph representation; cryptocurrency; transaction network
【摘要】以太坊作为全球最大的支持智能合约的公共区块链平台，自2014年上线以来积累了大量的用户交易记录。然而，到目前为止，对以太坊交易记录的分析还相对较少。将交易记录建模为静态的简单图，现有方法无法准确刻画边缘的时代性和多路性特征。在本文中，我们首先通过结合交易的时间和数量特征，将以太坊交易记录建模为一个复杂的网络，然后为这个大规模网络的基于随机行走的图表示设计几个灵活的时间行走策略。基于真实以太坊数据的时间链预测实验表明，时间信息和边缘的多重特性对于准确建模和理解以太坊交易网络是不可或缺的。
【关键词】复杂网络;数据挖掘;电路与系统;聪明的合同;数据模型;区块链;社交网络(网络);以太坊;区块链;复杂网络;图表示;加密货币;交易网络
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