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 longestrunning 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.
Pastrana, S., Hutchings, A., Caines, A., & Buttery, P. (2018). Characterizing Eve: Analysing cybercrime actors in a large underground forum. Heraklion: The 21st International Symposium on Research in Attacks, Intrusions and Defenses (RAID).