This research explores how Large Language Models can transform cryptocurrency transaction analysis with enhanced interpretability and pattern recognition.

• Addresses limitations of current black-box analysis methods
• Applies LLMs to real-world Bitcoin transaction data
• Demonstrates improved ability to detect behavioral patterns
• Creates a framework for more transparent security monitoring

This breakthrough matters because it provides security professionals with more interpretable tools to identify fraudulent activities and money laundering in cryptocurrency networks, moving beyond opaque analysis methods toward AI-powered solutions that can adapt to evolving threats.

Original Paper: Large Language Models for Cryptocurrency Transaction Analysis: A Bitcoin Case Study