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http://dx.doi.org/10.4218/etrij.13.2013.0049

Game Bot Detection Approach Based on Behavior Analysis and Consideration of Various Play Styles  

Chung, Yeounoh (School of Information and Communication Engineering, Sungkyunkwan University)
Park, Chang-Yong (School of Information and Communication Engineering, Sungkyunkwan University)
Kim, Noo-Ri (School of Information and Communication Engineering, Sungkyunkwan University)
Cho, Hana (School of Information and Communication Engineering, Sungkyunkwan University)
Yoon, Taebok (Department of Computer Software, Seoil University)
Lee, Hunjoo (Creative Content Research Laboratory, ETRI)
Lee, Jee-Hyong (School of Information and Communication Engineering, Sungkyunkwan University)
Publication Information
ETRI Journal / v.35, no.6, 2013 , pp. 1058-1067 More about this Journal
Abstract
An approach for game bot detection in massively multiplayer online role-playing games (MMORPGs) based on the analysis of game playing behavior is proposed. Since MMORPGs are large-scale games, users can play in various ways. This variety in playing behavior makes it hard to detect game bots based on play behaviors. To cope with this problem, the proposed approach observes game playing behaviors of users and groups them by their behavioral similarities. Then, it develops a local bot detection model for each player group. Since the locally optimized models can more accurately detect game bots within each player group, the combination of those models brings about overall improvement. Behavioral features are selected and developed to accurately detect game bots with the low resolution data, considering common aspects of MMORPG playing. Through the experiment with the real data from a game currently in service, it is shown that the proposed local model approach yields more accurate results.
Keywords
User behavior analysis; machine learning; bot detection model; MMORPGs; game play styles;
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