Fraud and Bot Detection in Gaming Marketplaces
Abstract
Cloud-scale game marketplaces face increas-ing threats from automated activity and coordinated abuse, including repeated redemption of gift coupons and single- use discount codes, as well as the creation of free or secondary accounts to inherit starter currencies or in- game assets. This paper surveys practical detection ap- proaches suitable for real-time production environments, emphasizing observable system signals rather than model- heavy or AI-driven methods. We describe techniques for monitoring API call sequences and rates, simple behav- ioral signals such as keystroke latency, and graph-based linkage analysis to detect clusters of accounts exploit- ing shared vouchers or resource transfers. Operational tradeoffs including latency, privacy, and computational cost are discussed, along with strategies for mitigating abuse through tiered interventions. This work provides a framework for deploying effective fraud detection while preserving legitimate user experience in rapidly evolving game marketplaces.
Fields of Study & Subjects
Spam and Phishing Detection
Cybercrime and Law Enforcement Studies
Network Security and Intrusion Detection
Publication details
- Journal / source
- International Journal of Artificial Intelligence Data Science and Machine Learning
- Volume
- 7
- Issue
- 1
- Pages
- 116–119
- Publication date
- 1 January 2026
- Language
- EN