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One for all: A comprehensive graph structure of the account-based blockchain for multi-view analysis
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DOI：10.1016/j.ipm.2025.104556.png)
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Abstract
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Transactions and addresses on account-based blockchains form highly interconnected networks. However, current methods face several challenges, as incomplete graph structures inadequately support specific analytical tasks and are inefficient for certain time-sensitive analyses. In this paper, we propose a multi-view comprehensive graph structure in account-based blockchains to overcome these challenges. Specifically, we deploy archive nodes to extract various raw data from the account-based blockchain and construct the basic graph structure. Meanwhile, we analyze the initiating reasons of transactions to form the intrinsic attribute view. Then, we further analyze the on-chain activities of addresses and annotate the edges within the graph to form a view of common behaviors. Our comprehensive graph structure includes the two views mentioned above, which not only supports analyses within a single view but also enables the exploration of correlations between different views. The proposed graph structure achieves an average speed improvement of 49.08% compared to baselines in experiments. Through multi-view ecosystem analyses, we provide insights into the blockchain characteristics. We demonstrate the application of the comprehensive graph to multi-view analytical tasks on account-based blockchains, including forensics of ”the DAO attack”, phishing detection, and address classification as examples. As a result, we find 13 unreported potential DAO attacker accounts, and outperform existing graph structures in various downstream tasks.
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