With the widespread adoption of cross-chain bridges and decentralized swapping protocols, an increasing number of money laundering activities leverage multi-chain hopping to obscure the origin and flow of illicit funds. However, most existing public blockchain anti-money laundering datasets focus on transactions within a single blockchain, lacking a systematic characterization of cross-chain fund flows. This limitation significantly constrains the analysis of cross-chain money laundering behaviors and the development and evaluation of related detection methods.

Objective
This project has two main objectives: (1) to design and implement a pipeline for constructing a cross-chain money laundering dataset by parsing cross-chain bridge-related behaviors from real-world blockchain transaction data, reconstructing cross-chain fund flow paths, and producing a structured and reproducible dataset; and (2) to analyze the characteristics of cross-chain money laundering behaviors based on the constructed dataset, summarizing typical patterns in terms of fund transfer strategies and inter-chain hopping behaviors.