This paper addresses the gap in research on private interactions within underground forums and marketplaces, which are critical for understanding cybercrime workflows. By analyzing a leaked dataset from Nulled.io, the study explores the content and purposes of private messages. Additionally, it develops machine learning models that utilize publicly available data to detect private communications between users, along with adversarial analysis to assess the robustness of these detection methods.
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Sun, Zhibo, et al. "Understanding and predicting private interactions in underground forums." Proceedings of the Ninth ACM Conference on Data and Application Security and Privacy. 2019.
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