Stateless Puzzles for Real Time Online Fraud Preemption
Open accessAbstract
The profitability of fraud in online systems such as app markets and social networks marks the failure of existing defense mechanisms. In this paper, we propose FraudSys, a real-time fraud preemption approach that imposes Bitcoin-inspired computational puzzles on the devices that post online system activities, such as reviews and likes. We introduce and leverage several novel concepts that include (i) stateless, verifiable computational puzzles, that impose minimal performance overhead, but enable the efficient verification of their authenticity, (ii) a real-time, graph based solution to assign fraud scores to user activities, and (iii) mechanisms to dynamically adjust puzzle difficulty levels based on fraud scores and the computational capabilities of devices. FraudSys does not alter the experience of users in online systems, but delays fraudulent actions and consumes significant computational resources of the fraudsters. Using real datasets from Google Play and Facebook, we demonstrate the feasibility of FraudSys by showing that the devices of honest users are minimally impacted, while fraudster controlled devices receive daily computational penalties of up to 3,079 hours. In addition, we show that with FraudSys, fraud does not pay off, as a user equipped with mining hardware (e.g., AntMiner S7) will earn less than half through fraud than from honest Bitcoin mining.
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A one-star rating boost was shown to increase restaurant revenue by 5-9%.
“For example, a one star boost in rating was shown to help restaurants increase revenue by a 5-9% margin [46].”
From Fraud De-Anonymization for Fun and Profit (2018) · cites this paper as [46]
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Cites
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Fraud De-Anonymization for Fun and Profit
Hernandez, N., Rahman, M., Recabarren, R., & Carbunar, B. (2018) · Proceedings of the 2018 ACM SIGSAC Conference on Computer and Communications Security · doi:10.1145/3243734.3243770 · Cited by 16 · see citing works
Self-citation
- Authors
- Rahman, M., Recabarren, R., Carbunar, B., & Lee, D.
- Affiliations
- Florida International University (US)
- Pennsylvania State University (US)
- Venue
- Proceedings of the 2017 ACM on Web Science Conference
- Publisher
- ACM
- Published
- 2017-06-25
- Pages
- 23-32
- OpenAlex
- W2623819121
- Cited by
- 4
- References
- 14
- Citations by year
- 2021: 1 · 2020: 1 · 2018: 2
- FWCI
- 0.63
- Type
- conference paper
- Language
- en
- Open access
- green
- arxiv.org
- Locations
- ACM Web Science Conference (WebSci) (publishedVersion)
- arXiv (Cornell University) (submittedVersion)
- arXiv (Cornell University)
- Funders
- NSF (CNS-1527153, CNS-1422215, SES-1450619, IUSE-1525601)
- Samsung (GRO 2015)
- Topics
- Physical Sciences › Computer Science › Information Systems › Spam and Phishing Detection
- Physical Sciences › Computer Science › Information Systems › Cybercrime and Law Enforcement Studies
- Physical Sciences › Computer Science › Information Systems › Blockchain Technology Applications and Security
- Keywords
- online fraud, fraud detection, user-generated content, App Store, social networks, Google Play Store, Facebook, computational overhead, fraudsters
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