Understanding Underground Incentivized Review Services

TL;DR

This study investigates the motivations, techniques, and resilience of underground incentivized review services on e-commerce platforms through surveys with fraudsters, revealing sophisticated operations and effective countermeasures.

Contribution

It provides the first detailed insights into fraudster operations and motivations in incentivized review services, highlighting their use of AI tools and resistance to takedown efforts.

Findings

Fraudsters use AI tools like ChatGPT for review generation.

Communication channel restrictions effectively reduce incentivized reviews.

Fraud operations are sophisticated, scalable, and resistant to removal.

Abstract

While human factors in fraud have been studied by the HCI and security communities, most research has been directed to understanding either the victims' perspectives or prevention strategies, and not on fraudsters, their motivations and operation techniques. Additionally, the focus has been on a narrow set of problems: phishing, spam and bullying. In this work, we seek to understand review fraud on e-commerce platforms through an HCI lens. Through surveys with real fraudsters (N=36 agents and N=38 reviewers), we uncover sophisticated recruitment, execution, and reporting mechanisms fraudsters use to scale their operation while resisting takedown attempts, including the use of AI tools like ChatGPT. We find that countermeasures that crack down on communication channels through which these services operate are effective in combating incentivized reviews. This research sheds light on the complex landscape of incentivized reviews, providing insights into the mechanics of underground services and their resilience to removal efforts.