以太坊交互图上的行为感知账户去匿名化
Behavior-aware Account De-anonymization on Ethereum Interaction Graph
摘要：
区块链技术具有去中心化、可追溯、防篡改的特点，打造了一个可靠的去中心化信任机制，进一步加速了区块链金融的发展。然而，区块链的匿名化阻碍了市场监管，导致区块链金融平台上洗钱、赌博、钓鱼欺诈等违法行为日益增多。因此，金融安全已成为区块链生态系统的重中之重，需要有效的市场监管。本文从图分类的角度考虑以太坊账户的识别问题，提出了一个端到端的图神经网络框架Ethident，用来刻画账户的行为模式，进而实现账户的去匿名化。具体来说，我们首先使用原始以太坊数据构建账户交互图（AIG）。然后设计了一个层次化的图注意编码器HGATE作为框架的主干，它可以有效地刻画节点级账户特征和子图级行为模式。为了缓解账户标签稀缺，我们进一步引入对比自我监督机制作为规范，共同训练我们的框架。在以太坊数据集上的综合实验表明，我们的框架在账户识别方面取得了优异的性能，相对于以前的最先进技术，获得了1.13% ~ 4.93%的相对提高。此外，详细的分析说明了Ethident在识别和理解以太坊中已知参与者（例如交易所，矿工等）的行为方面的有效性，以及违法者（例如网络钓鱼诈骗者、黑客等）的信息，这有助于风险评估和市场监管。
英文摘要：
Blockchain technology has the characteristics of decentralization, traceability and tamper-proof, which creates a reliable decentralized trust mechanism, further accelerating the development of blockchain finance. However, the anonymization of blockchain hinders market regulation, resulting in increasing illegal activities such as money laundering, gambling and phishing fraud on blockchain financial platforms. Thus, financial security has become a top priority in the blockchain ecosystem, calling for effective market regulation. In this paper, we consider identifying Ethereum accounts from a graph classification perspective, and propose an end-to-end graph neural network framework named Ethident, to characterize the behavior patterns of accounts and further achieve account de-anonymization. Specifically, we first construct an Account Interaction Graph (AIG) using raw Ethereum data. Then we design a hierarchical graph attention encoder named HGATE as the backbone of our framework, which can effectively characterize the node-level account features and subgraph-level behavior patterns. For alleviating account label scarcity, we further introduce contrastive self-supervision mechanism as regularization to jointly train our framework. Comprehensive experiments on Ethereum datasets demonstrate that our framework achieves superior performance in account identification, yielding 1.13% ~ 4.93% relative improvement over previous state-of-the-art. Furthermore, detailed analyses illustrate the effectiveness of Ethident in identifying and understanding the behavior of known participants in Ethereum (e.g. exchanges, miners, etc.), as well as that of the lawbreakers (e.g. phishing scammers, hackers, etc.), which may aid in risk assessment and market regulation.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
