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http://dx.doi.org/10.13089/JKIISC.2012.22.2.225

User Behavior Analysis for Online Game Bot Detection  

Kang, Ah-Reum (Graduate School of Information Security, Korea University)
Woo, Ji-young (Graduate School of Information Security, Korea University)
Park, Ju-yong (Physics Department, College of Sciences, Kyunghee University)
Kim, Huy-Kang (Graduate School of Information Security, Korea University)
Publication Information
Journal of the Korea Institute of Information Security & Cryptology / v.22, no.2, 2012 , pp. 225-238 More about this Journal
Abstract
Among the various security threats in online games, the use of game bots is the most serious problem. In this paper, we propose a framework for user behavior analysis for bot detection in online games. Specifically, we focus on party play that reflects the social activities of gamers: In a Massively Multi-user Online Role Playing Game (MMORPG), party play log includes a distinguished information that can classify game users under normal-user and abnormal-user. That is because the bot users' main activities target on the acquisition of cyber assets. Through a statistical analysis of user behaviors in game activity logs, we establish the threshold levels of the activities that allow us to identify game bots. Also, we build a knowledge base of detection rules based on this statistical analysis. We apply these rule reasoner to the sixth most popular online game in the world. As a result, we can detect game bot users with a high accuracy rate of 95.92%.
Keywords
Online game security; game bot; user behavior analysis; MMORPG;
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