Understanding and Predicting Private Interactions in Underground Forums.

The studies on underground forums and marketplaces have significantly advanced our understandings of cybercrime workflows and underground economies. Researchers of underground economies have conducted comprehensive studies on public interactions. However, little research focuses on private interactions. The lack of the investigation on private interactions may cause misunderstandings on underground economies, as users in underground forums and marketplaces tend to share the minimal amount of information in public interactions and resort to private messages for follow-up conversations. In this paper, we propose methods to investigate the underground private interactions and we analyze a recently leaked dataset from Nulled.io. We present analyses on the contents and purposes of private messages. In addition, we design machine learning-based models that only use the publicly available information to detect if two underground users privately communicate with each other. Finally, we perform adversarial analysis to evaluate the robustness of the detector to different types of attacks.