Lifestyles of Virtual World Residents, Living in the on-line game, "Lineage"
CW '03 Proceedings of the 2003 International Conference on Cyberworlds
The social side of gaming: a study of interaction patterns in a massively multiplayer online game
CSCW '04 Proceedings of the 2004 ACM conference on Computer supported cooperative work
Detection of MMORPG bots based on behavior analysis
ACE '08 Proceedings of the 2008 International Conference on Advances in Computer Entertainment Technology
Identifying MMORPG bots: a traffic analysis approach
EURASIP Journal on Advances in Signal Processing - Special issue on signal processing applications in network intrusion detection systems
Game bot identification based on manifold learning
Proceedings of the 7th ACM SIGCOMM Workshop on Network and System Support for Games
Networked Graphics: Building Networked Games and Virtual Environments
Networked Graphics: Building Networked Games and Virtual Environments
Session-based classification of internet applications in 3G wireless networks
Computer Networks: The International Journal of Computer and Telecommunications Networking
Game behavior pattern modeling for game bots detection in MMORPG
Proceedings of the 4th International Conference on Uniquitous Information Management and Communication
ICONIP'12 Proceedings of the 19th international conference on Neural Information Processing - Volume Part V
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Auto-playing programs are often used on behalf of human players in a MMORPG(Massively Multi-player Online Role Playing Game). By playing automatically and continuously, it helps to speed up the game character’s level-up process. However, the auto-playing programs, either software or hardware, do harm to games servers in various ways including abuse of resources. In this paper, we propose a way of detecting the auto programs by analyzing the window event sequences produced by the game players. In our proposed method, the event sequences are transformed into a set of attributes, and various learning algorithms are applied to classify the data represented by the set of attribute values into human or auto player. The results from experiments with several MMORPGs show that the Decision Tree learning with proposed method can identify the auto-playing programs with high accuracy.