Forensic analysis of a graph depicting Bitcoin blockchain transaction data has revealed illicit activity and money laundering clusters.

The forensic analysis also detected criminal proceeds from crypto exchanges on the Russian darknet market. The discovery was made by Elliptic with help from researchers in the MIT-IBM Watson AI lab. The findings were discovered within a dataset titled Elliptic2, which depicted the Bitcoin clusters using 122k labeled subgraphs. Elliptic2 is the second version of the Elliptic Data Set (Elliptic1), invented to document and combat financial crime. The goal of the dataset is to reveal illicit activity by utilizing the blockchain’s pseudonymity in collaboration with knowledge regarding the presence of illicit activity recognition and illicit services. Researchers utilize machine learning supplemented by patterns of transactions that illustrate forms of money laundering to build knowledge. This enables the prediction of crypto transactions that could potentially be illicit in nature and constitute criminal activity. This type of forensic analysis also enables the ability to trace the source of the illicit funds. The “shape” of the clusters has proved effective in alerting to illicit activity. Future research will maintain a focus on improving the accuracy and precision of identifying criminal leads.

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