1 citations · 1 across the 4 of their papers we have counts for
4 papers
Knowledge-Integrated Representation Learning for Crypto Anomaly Detection under Extreme Label Scarcity; Relational Domain-Logic Integration with Retrieval-Grounded Context and Path-Level Explanations
Gyuyeon Na, Minjung Park, Soyoun Kim +2
Detecting anomalous trajectories in decentralized crypto networks is fundamentally challenged by extreme label scarcity and the adaptive evasion strategies of illicit actors. While…
Improving Cryptocurrency Pump-and-Dump Detection through Ensemble-Based Models and Synthetic Oversampling Techniques
Jieun Yu, Minjung Park, Sangmi Chai
This study aims to detect pump and dump (P&D) manipulation in cryptocurrency markets, where the scarcity of such events causes severe class imbalance and hinders accurate detection…
Hybrid GCN-GRU Model for Anomaly Detection in Cryptocurrency Transactions
Gyuyeon Na, Minjung Park, Hyeonjeong Cha +6
Blockchain transaction networks are complex, with evolving temporal patterns and inter-node relationships. To detect illicit activities, we propose a hybrid GCN-GRU model that capt…
HyPV-LEAD: Proactive Early-Warning of Cryptocurrency Anomalies through Data-Driven Structural-Temporal Modeling
Minjung Park, Gyuyeon Na, Soyoun Kim +3
Abnormal cryptocurrency transactions - such as mixing services, fraudulent transfers, and pump-and-dump operations -- pose escalating risks to financial integrity but remain notori…