ATM-GAD detects fraudulent accounts by combining per-account adaptive time windows, temporal three-node motifs, and two attention layers, reporting state-of-the-art AUPRC across four financial datasets.
XBLOCK Blockchain Datasets: InPlusLab ethereum phishing detection datasets
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ATM-GAD: Adaptive Temporal Motif Graph Anomaly Detection for Financial Transaction Networks
ATM-GAD detects fraudulent accounts by combining per-account adaptive time windows, temporal three-node motifs, and two attention layers, reporting state-of-the-art AUPRC across four financial datasets.