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 Network-based Crypto Asset Analysis |  | CHENG Ling PhD Candidate
School of Computing and Information Systems
Singapore Management University
| Research Area Dissertation Committee Research Advisor Committee Members External Member - WANG Yong, Assistant Professor, College of Computing and Data Science, Nanyang Technological University
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| | Date 22 April 2025 (Tuesday) | Time 2:00pm - 3:00pm | Venue Meeting room 4.4,
Level 4
School of Computing and Information Systems 1,
Singapore Management University,
80 Stamford Road
Singapore 178902 | Please register by 21 April 2025. We look forward to seeing you at this research seminar. 
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| | ABOUT THE TALK This thesis presents a comprehensive framework for early detection of malicious activities in the Bitcoin network by analyzing four key properties: decentralization, fluidity, connectivity, and regularity. A 15-year transaction dataset is used to explore asset control distribution and dynamic transaction behaviors. The proposed Evolve Path Tracer leverages asset transfer paths and graph neural networks to detect fraud in fast-evolving, sparse networks. Enhancing this, the Intention Monitor introduces interpretability and intent prediction through behavioral analysis. Together, these models address limitations in current methods by offering scalable, interpretable, and proactive fraud detection to safeguard cryptocurrency ecosystems. | | | SPEAKER BIOGRAPHY CHENG Ling is a Ph.D. Candidate in Computer Science at the SMU SCIS, supervised by Prof. Feida ZHU. His research interests are Early Anomaly Detection and Community Detection in Cryptocurrency. |
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