Visible to the public Search Rank Fraud De-Anonymization in Online Systems

TitleSearch Rank Fraud De-Anonymization in Online Systems
Publication TypeConference Paper
Year of Publication2018
AuthorsRahman, Mizanur, Hernandez, Nestor, Carbunar, Bogdan, Chau, Duen Horng
Conference NameProceedings of the 29th on Hypertext and Social Media
Conference LocationNew York, NY, USA
ISBN Number978-1-4503-5427-1
Keywordsanonymity, composability, fraud de-anonymization, Human Behavior, human factors, Metrics, pubcrawl, resilience, Resiliency, search rank fraud

We introduce the fraud de-anonymization problem, that goes beyond fraud detection, to unmask the human masterminds responsible for posting search rank fraud in online systems. We collect and study search rank fraud data from Upwork, and survey the capabilities and behaviors of 58 search rank fraudsters recruited from 6 crowdsourcing sites. We propose Dolos, a fraud de-anonymization system that leverages traits and behaviors extracted from these studies, to attribute detected fraud to crowdsourcing site fraudsters, thus to real identities and bank accounts. We introduce MCDense, a min-cut dense component detection algorithm to uncover groups of user accounts controlled by different fraudsters, and leverage stylometry and deep learning to attribute them to crowdsourcing site profiles. Dolos correctly identified the owners of 95% of fraudster-controlled communities, and uncovered fraudsters who promoted as many as 97.5% of fraud apps we collected from Google Play. When evaluated on 13,087 apps (820,760 reviews), which we monitored over more than 6 months, Dolos identified 1,056 apps with suspicious reviewer groups. We report orthogonal evidence of their fraud, including fraud duplicates and fraud re-posts.

Citation KeyrahmanSearchRankFraud2018