Due to the widespread use of smart contracts, Ethereum has become the second-largest blockchain platform after Bitcoin. Many different types of Ethereum accounts (ICO, Mining, Gambling, etc.) also have quite active trading activities on Ethereum. Studying the transaction records of these specific Ethereum accounts is very important for understanding their particular transaction characteristics, and further labeling the pseudonymous accounts. However, traditional methods are generally based on static and global transaction networks to conduct research, ignoring useful information about dynamic changes. Our work chooses six kinds of important account labels, and builds ego networks for each kind of Ethereum account. We focus on the interaction between the target node and neighbor nodes with temporal analysis. Experiments show that there is a significant difference between various types of accounts in terms of several network features, helping us better understand their transaction patterns. To the best of our knowledge, this is the first work to analyze the dynamic characteristics of Ethereum labeled accounts from the perspective of transaction ego networks.
翻译:由于广泛使用智能合同,Eceenum已成为Bitcoin之后第二大链条平台。许多不同类型的Eceenum账户(ICO, Mining, Gambling等)在Eceenum上也有相当活跃的交易活动。研究这些特定的Eceenum账户的交易记录对于了解其具体交易特点和进一步标注假名账户非常重要。然而,传统方法通常基于静态和全球交易网络开展研究,忽视关于动态变化的有用信息。我们的工作选择了六类重要账户标签,并为每一种Etheenum账户建立了自我网络。我们侧重于目标节点与邻接节点之间的互动,同时进行时间分析。实验表明,不同类型账户在几个网络特征方面有很大差异,帮助我们更好地了解其交易模式。据我们所知,这是从交易自我网络的角度分析Eceen标签账户动态特征的首项工作。