MT²AD: multi-layer temporal transaction anomaly detection in ethereum networks with GNN

Key Points

• Anomaly detection in ethereum networks reveals unusual transaction patterns, enhancing security measures.
• The analysis identifies these anomalies using a graph neural network model designed for temporal data.
• Employing graph neural networks provides a robust framework for detecting temporal transaction anomalies.
• The findings highlight the potential for improved transaction security, indicating a need for further investigation.