Following Their Footsteps: Characterizing Account Automation Abuse and Defenses

Internet Measurement Conference (ICM)

By: Louis F. DeKoven, Trevor Pottinger, Stefan Savage, Geoffrey M. Voelker, Nektarios Leontiadis

Abstract

Online social networks routinely attract abuse from for-profit services that offer to artificially manipulate a user’s social standing. In this paper, we examine five such services in depth, each advertising the ability to inflate their customer’s standing on the Instagram social network. We identify the techniques used by these services to drive social actions, and how they are structured to evade straightforward detection. We characterize the dynamics of their customer base over several months and show that they are able to attract a large clientele and generate over $1M in monthly revenue. Finally, we construct controlled experiments to disrupt these services and analyze how different approaches to intervention (i.e., transparent interventions such as blocking abusive services vs. more opaque approaches such as deferred removal of artificial actions) can drive different reactions and thus provide distinct trade-offs for defenders.