China's AI System Accurately Identifies Illicit Bitcoin Transactions
Chinese researchers have developed an AI system that can identify illicit Bitcoin transactions with high accuracy. The team from China's top police university, the People's Public Security University of China, published their findings in May in the Journal of Intelligence.
The AI framework combines three technologies: dynamic graph neural networks, a memory module that stores historical patterns of illicit activity, and large language models for reasoning and classification.
The researchers tested their system on the Elliptic Bitcoin dataset, which contains 203,769 transaction nodes and 234,355 edges connecting them. The model achieved 89.1% precision and a 64.5% recall rate specifically for illicit transactions.
Dr. Sun Jingchao, the study's corresponding author, pointed to the system's historical pattern matching capabilities as a key advantage. The framework also produces natural language explanations for its decisions, which could be useful for regulators and prosecutors who need evidence that holds up in court.