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http://dx.doi.org/10.7583/JKGS.2011.11.6.081

Online Game Identity Theft Detection Model based on Hacker's Behavior Analysis  

Choi, Hwa-Jae (Graduate School of Information Security, Korea University)
Woo, Ji-Young (Graduate School of Information Security, Korea University)
Kim, Huy-Kang (Graduate School of Information Security, Korea University)
Publication Information
Journal of Korea Game Society / v.11, no.6, 2011 , pp. 81-93 More about this Journal
Abstract
Identity theft happens frequently in popular MMORPG(Massively Multi-player Online Role Playing Games) where profits can be gained easily. In spite of the importance of security about identity theft in MMORPG, few methods to prevent and detect identity theft in online games have been proposed. In this study, we investigate real identity theft cases of an online game and define the representative patterns of identity theft as the speedy type, cautious type, and bold type. We then propose the automatic identity theft detection model based on the multi-class classification. We verify the system with one of the leading online games in Korea. The multi-class detection model outperforms the existing binary-class one(hacked or not).
Keywords
Online Game Security; Identity Theft Detection; MMORPG; Neural Network; Behavior Analysis;
Citations & Related Records
Times Cited By KSCI : 2  (Citation Analysis)
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