Fraud and Bot Detection in Gaming Marketplaces

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Authors: Anand Ganesh
Cited by: 0

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