University of Twente Student Theses


Using stylometry to track cybercriminals in darknet forums

Ekambaranathan, Anirudh (2018) Using stylometry to track cybercriminals in darknet forums.

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Abstract:Darknet markets are becoming increasingly popular, making it important for law enforcement agencies to be aware of state of the art techniques on tracking and analysing key participants. In this work, we present an unsupervised method for linking user pseudonyms based on stylometry. We show on a Twitter dataset of 1,000 users that our method is 98.7\% accurate. We also construct a dataset containing the user migration after a darknet market closure. Subsequently, we use this dataset to show that our linking technique can be used to track displacement of users, even when ground truth data is not readily available. The results show that using bi-grams as input features, linkability can be achieved on a large scale. Even though effective linkability requires a minimum of 25 posts per user, we can still link a majority of active members in darknet market migrations. We also test five countermeasures to evade our linking technique and show that none of the measures would uphold if law enforcement agencies decided to perform dedicated linkage attacks.
Item Type:Essay (Master)
Faculty:EEMCS: Electrical Engineering, Mathematics and Computer Science
Subject:54 computer science
Programme:Computer Science MSc (60300)
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