Publication: MT²AD: multi-layer temporal transaction anomaly detection in ethereum networks with GNN
MT²AD: multi-layer temporal transaction anomaly detection in ethereum networks with GNN
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Han, B., Wei, Y., Wang, Q., De Collibus, F. M., & Tessone, C. J. (2024). MT²AD: multi-layer temporal transaction anomaly detection in ethereum networks with GNN. Complex & Intelligent Systems, 10(1), 613–626. https://doi.org/10.1007/s40747-023-01126-z
Abstract
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Abstract
In recent years, a surge of criminal activities with cross-cryptocurrency trades have emerged in Ethereum, the second-largest public blockchain platform. Most of the existing anomaly detection methods utilize the traditional machine learning with feature engineering or graph representation learning technique to capture the information in transaction network. However, these methods either ignore the timestamp information and the transaction flow direction information in transaction network or only consider single transaction network, t
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- Han, Beibei
- Wei, Yingmei
- Wang, Qingyong
- De Collibus, Francesco Maria
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Han, B., Wei, Y., Wang, Q., De Collibus, F. M., & Tessone, C. J. (2024). MT²AD: multi-layer temporal transaction anomaly detection in ethereum networks with GNN. Complex & Intelligent Systems, 10(1), 613–626. https://doi.org/10.1007/s40747-023-01126-z
