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http://dx.doi.org/10.13089/JKIISC.2018.28.5.1153

Game Bot Detection Based on Action Time Interval  

Kang, Yong Goo (Graduate School of Information Security, Korea University)
Kim, Huy Kang (Graduate School of Information Security, Korea University)
Publication Information
Journal of the Korea Institute of Information Security & Cryptology / v.28, no.5, 2018 , pp. 1153-1160 More about this Journal
Abstract
As the number of online game users increases and the market size grows, various kinds of cheating are occurring. Game bots are a typical illegal program that ensures playtime and facilitates account leveling and acquisition of various goods. In this study, we propose a method to detect game bots based on user action time interval (ATI). This technique observes the behavior of the bot in the game and selects the most frequent actions. We distinguish between normal users and game bots by applying Machine Learning to feature frequency, ATI average, and ATI standard deviation for each selected action. In order to verify the effectiveness of the proposed technique, we measured the performance using the actual log of the 'Aion' game and showed an accuracy of 97%. This method can be applied to various games because it can utilize all actions of users as well as character movements and social actions.
Keywords
Online Game; Bot Detection; Machine Learning;
Citations & Related Records
Times Cited By KSCI : 3  (Citation Analysis)
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1 A. Fujita, H. Itsuki, and H. Matsubara, "Detecting Real Money Traders in MMORPG by Using Trading Network," AIIDE'11, pp. 26-31, Oct. 2011.
2 E. CASTRONOVA. Effects of botting on world of warcraft. http://virtuallyblind.com/files/mdy/blizzard_msj_exhibit_7.pdf, 2007.
3 Jiyoung Woo and Huy Kang Kim. "Research Trend of Detection of Cheating in Online games," REVIEW OF KIISC, 27(4), pp. 14-21, 2017.
4 R. Thawonmas, Y. Kashifuji, and K.-T. Chen, "Detection of MMORPG Bots based on Behavior Analysis," ACE'08, pp. 91-94, Dec. 2008.
5 K.-T. Chen, A. Liao, H.-K. K. Pao, and H.-H. Chu, "Game Bot Detection Based on Avatar Trajectory," ICEC'08, vol. 5309, pp. 94-105, Sep. 2009.
6 M. van Kesteren, J. Langevoort, and F. Grootjen, "A Step in the Right Detecting: Bot Detection in MMORPG using Movement Analysis," The 21st Benelux Conference on Artificial Intelligence, 2009.
7 S. Mitterhofer, C. Kruegel, E. Kirda, and C. Platzer, "Server-side Bot Detection in Massively Multiplayer Online Games," IEEE Security & Privacy, vol. 7, no.3, pp. 29-36, May 2009.
8 Kuan-Ta Chen, Li-Wen Hong. "User identification based on game-play activity patterns," ACM SIGCOMM workshop on Network and system support for games, pp. 7-12, Sep. 2007.
9 Jina Lee, Jiyoun Lim, Wonjun Cho, Huy Kang Kim, "I know what the BOTs did yesterday: Full action sequence analysis using Naive Bayesian algorithm," Annual Workshop on Network and Systems Support for Games, pp. 1-2, Dec. 2013.
10 Eunjo Lee, Jiyoung Woo, Hyoungshick Kim, Aziz Mohaisen, and Huy Kang Kim, "You are a Game Bot!: Uncovering Game Bots in MMORPGs via Self-similarity in the Wild." NDSS. 2016.
11 B. Keegan, M. A. Ahmad, J. Srivastava, D. Williams, and N. Contractor, "Dark Gold: Statistical Properties of Clandestine Networks in Massively Multiplayer Online Games," IEEE Second International Conference on Social Computing, pp. 201-208, Aug. 2010.
12 M. A. Ahmad, B. Keegan, J. Strivastava, D. Williams, and N. Contractor, "Mining for Gold Farmers: Automatic Detection of Deviant Players in MMOGs," International Conference on Computational Science and Engineering, vol. 4. pp. 340-345, Aug. 2009.
13 Ah Reum Kang, Jiyoung Woo, Juyong Park, and Huy Kang Kim, "Online game bot detection based on party-play log analysis," Computers & Mathematics with Applications, vol. 65, no. 9, pp. 1384-1395, May 2013.   DOI
14 Y. Chung, C. yong. Park, N. ri, Kim, H. Cho, T. Yoon, H. Lee, and J. -H. Lee, "Game Bot Detection Approach Based on Behavior Analysis and Consideration of Various Play Style," in Journal of ETRI, vol. 35, no. 6, pp. 1058-1067, Dec. 2013.   DOI
15 Jae-hyuk Lee, Sung Wook Kang, and Huy Kang Kim, "Detecting malicious behaviors in MMORPG by applying motivation theory," Journal of Korea Game Society, vol. 15, no. 4, pp. 69-78, Aug. 2015.   DOI
16 J. Woo, A. Kang, and H. K. Kim, "The Contagion of Malicious Behaviors in Online Game," Computer Communication Review, vol. 43, pp. 543-544, 2013.   DOI
17 H. Kwon, A. Mohaisen, J. Woo, Y. Kim, and H. K. Kim, "Crime Scene Reconstruction: Online Gold Farming Network Analysis," IEEE Transactions on Information Forensics and Security, vol. 12, no. 3, pp. 544-556, Nov. 2016.   DOI
18 A. R. Kang, H. K. Kim, and J. Woo, "Chatting Pattern Based Game Bot Detection: Do They Talk Like Us?," KSII Transactions on Internet and Information Systems, vol. 6, no. 11, pp. 2866-2879, Nov. 2012.   DOI
19 Ah Reum Kang, Seong Hoon Jeong, Aziz Mohaisen, and Huy Kang Kim, "Multimodal game bot detection using user behavioral characteristics." SpringerPlus, 5(1), 523, 2016.   DOI
20 https://venturebeat.com/2013/11/25/more-than-1-2-billion-people-are-playing-games
21 https://www.statista.com/statistics/267190/traffic-forecast-for-internet-gaming
22 https://www.statista.com/statistics/308454/gaming-revenue-countries