Catching Loosely Synchronized Behavior in Face of Camouflage

TL;DR

This paper addresses the challenge of detecting loosely synchronized fraudulent behaviors in online social platforms, especially when fraudsters use camouflage tactics to evade detection mechanisms.

Contribution

It introduces a novel method for identifying loosely synchronized fraudulent activities despite camouflage strategies used by fraudsters.

Findings

Effective detection of loosely synchronized fraud behaviors

Robustness against camouflage tactics

Improved accuracy over existing methods

Abstract

Fraud has severely detrimental impacts on the business of social networks and other online applications. A user can become a fake celebrity by purchasing "zombie followers" on Twitter. A merchant can boost his reputation through fake reviews on Amazon. This phenomenon also conspicuously exists on Facebook, Yelp and TripAdvisor, etc. In all the cases, fraudsters try to manipulate the platform's ranking mechanism by faking interactions between the fake accounts they control and the target customers.