ETX2Vec: a fraud detection algorithm for ethereum based on temporal biased random walk strategy.

Overview

1. College of Statistics and Data Science, Xinjiang University of Finance and Economics, Urumqi, 830012 PR China
2. Xinjiang Research Center for Socio-Economic Statistics and Big Data Applications, Urumqi, China
3. College of Big Data Statistics, Guizhou University of Finance and Economics, Guiyang, 550025 PR China
4. School of Public Health, Xinjiang Medical University, Urumqi, 830017 PR China

Abstract

Against the complex characteristics of the Ethereum transaction network and the limitations of existing graph embedding methods based on random walks, which fail to effectively capture transaction temporal dynamics and the flow of funds, we propose a fraud detection algorithm for Ethereum, ETX2Vec (Ethereum Transactions (TX) to Vector), which improves upon transaction subgraph construction and random walk strategies. First, in terms of transaction subgraph construction, we extract the first-order predecessor and successor neighboring nodes of the target node to reconstruct the transaction subgraph, enabling the random walk to effectively capture the complete flow of funds. Second, in the design of the random walk strategy, we introduce two key improvements: (1) the next node is selected based on the non-decreasing principle of transaction timestamps, effectively capturing the temporal dynamics of transactions within the network, and (2) a biased random walk strategy is designed based on both transaction timestamps and amounts, with a parameter introduced to control the weighting of these factors when calculating transition probabilities. Experimental results show that ETX2Vec achieves an average performance of 96.04% in downstream node classification tasks, outperforming the best model in similar studies by 3.74%, and even surpassing neural network models such as GAT and GCN. This demonstrates that ETX2Vec is more effective at understanding and processing the Ethereum transaction network, leading to the learning of high-quality node embedding vectors.

Reproduced under the paper's license (CC BY), from the paper cited above.

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Data

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Data availability

Datasets and source code are available from the GitHub repository: [https://github.com/Lujiarong1203/ETH2Vec](https:/github.com/Lujiarong1203/ETH2Vec) .

Reproduced under the paper's license (CC BY), from the paper cited above.

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Version 1, 29 September 2026: the first record

Recorded: type, language, journal, volume, issue, pages, dates, 4 authors, 7 keywords, 1 funder, 32 references.

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This paper

Lu, J., Liao, B., Liu, Y., & Zhong, L. (2026). ETX2Vec: a fraud detection algorithm for ethereum based on temporal biased random walk strategy. Scientific reports, 16(1), 16743. https://doi.org/10.1038/s41598-026-43153-z

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