What we do in the shadows: mining temporal motifs from transactions on the Dark Web

Dark web marketplaces are forums where users can buy or sell illicit goods/services and transactions are typically made using cryptocurrencies. While there have been numerous coordinated shutdowns of individual markets by authorities, the ecosystem has been found to be immensely resilient. In addition, while transactions are open and visible by anyone on the blockchain, the sheer scale of the data makes monitoring beyond basic characteristics a huge effort.

In this talk, I propose the use of temporal motif counting, as a way of monitoring both the system as a whole and the users within it. Focusing on the Alphabay and Hydra dark markets, I study all the motifs formed by three sequential transactions among two to three users, finding that they can tell us something more complex than can be captured by simply degree or transaction volume. Studying motifs local to the node, I show how users form salient clusters, which is a promising route for classification or anomaly detection tasks.