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Characterizing Eve: Analysing Cybercrime Actors in a Large Underground Forum

  • Sergio Pastrana
  • Alice Hutchings
  • Andrew Caines
  • Paula Buttery
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11050)

Abstract

Underground forums contain many thousands of active users, but the vast majority will be involved, at most, in minor levels of deviance. The number who engage in serious criminal activity is small. That being said, underground forums have played a significant role in several recent high-profile cybercrime activities. In this work we apply data science approaches to understand criminal pathways and characterize key actors related to illegal activity in one of the largest and longest-running underground forums. We combine the results of a logistic regression model with k-means clustering and social network analysis, verifying the findings using topic analysis. We identify variables relating to forum activity that predict the likelihood a user will become an actor of interest to law enforcement, and would therefore benefit the most from intervention. This work provides the first step towards identifying ways to deter the involvement of young people away from a career in cybercrime.

Keywords

Cybercrime Underground forums Social behaviour Criminal pathways 

Notes

Acknowledgements

We thank the anonymous reviewers for their insightful comments. We also thank our colleagues from the Cambridge Cybercrime Centre for access to the CrimeBB dataset and their invaluable feedback, and Flashpoint, for assistance relating to actors of interest. This work was supported by The Alan Turing Institute’s Defence and Security Programme [grant DS/SDS/1718/4]; and the UK Engineering and Physical Sciences Research Council (EPSRC) [grant EP/M020320/1].

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Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  1. 1.Cambridge Cybercrime Centre, Department of Computer Science and TechnologyUniversity of CambridgeCambridgeUK
  2. 2.Theoretical and Applied Linguistics, Faculty of Modern and Medieval LanguagesUniversity of CambridgeCambridgeUK
  3. 3.Natural Language and Information Processing, Department of Computer Science and TechnologyUniversity of CambridgeCambridgeUK

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