Encyclopedia of Computer Graphics and Games

Living Edition
| Editors: Newton Lee

Detecting and Preventing Online Game Bots in MMORPGs

  • Huy Kang KimEmail author
  • Jiyoung Woo
Living reference work entry
DOI: https://doi.org/10.1007/978-3-319-08234-9_13-1

Synonyms

Definition

Game users cheat to level up and accumulate cyber assets in an easy and fast manner without sufficient effort. One of the most widely used tools for cheating in online games is the game bot, which enables users to cheat in a convenient way by automatically performing the required actions. Therefore, game companies employ various security solutions for the detection and prevention of game bots.

Introduction

Online gaming is one of the successful Internet services. In the past few years, online games have become popular and have been generating huge profits. Online game companies generate profits by charging users a subscription fee and selling virtual items to them. Among the various types of games, MMORPGs (Massively Multiplayer Online Role Playing Games) make up one of the most popular genres.

As online games gain economic and social importance, various forms of threats emerge. A variety of methods have developed to parasitize...

Keywords

Online Game Online Gaming Human Player Game World Virtual Good 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
This is a preview of subscription content, log in to check access.

References

  1. Ahmad, M.A., Keegan, B., Sullivan, S., Williams, D., Srivastava, J., Contractor, N.: Illicit bits: Detecting and analyzing contraband networks in massively multiplayer online games, privacy, security, risk and trust (passat). IEEE third international conference on and 2011 I.E. third international conference on social computing (SocialCom), pp. 127–134 (2011)Google Scholar
  2. Ahmad, M.A., Keegan, B., Roy, A., Williams, D., Srivastava, J., Contractor, N.: Guilt by association? Network based propagation approaches for gold farmer detection, advances in social networks analysis and mining (ASONAM). IEEE/ACM International Conference on, pp. 121–126 (2013)Google Scholar
  3. Blackburn, J., Kourtellis, N., Skvoretz, J., Ripeanu, M., Iamnitchi, A.: Cheating in online games: a social network perspective. ACM Trans. Internet Technol. (TOIT) 13(9) (2014)Google Scholar
  4. Christensen, J., Cusick, M., Villanes, A., Veryovka, O., Watson, B., Rappa, M.: Win, Lose or Cheat: The Analytics of Player Behaviors in Online Games, Technical report (North Carolina State University. Dept. of Computer Science), 1–7 (2013)Google Scholar
  5. Chung, Y., Park, C.-y., Kim, N.-r., Cho, H., Yoon, T., Lee, H., Lee, J.-H.: Game bot detection approach based on behavior analysis and consideration of various play styles. ETRI J. 35, 1058–1067 (2013)CrossRefGoogle Scholar
  6. Corman, A.B.., Douglas, S., Schachte, P., Teague, V.: A secure event agreement (sea) protocol for peer-to-peer games, availability, reliability and security. The First International Conference on. 8 (2006)Google Scholar
  7. Davis, R.: Welcome to the new gold mines. The Guardian. 5, (2009)Google Scholar
  8. GauthierDickey, C., Zappala, D., Lo, V., Marr, J.: Low latency and cheat-proof event ordering for peer-to-peer games. In: Proceedings of the 14th International Workshop on Network and Operating Systems Support for Digital Audio and Video, pp. 134–139 (2004)Google Scholar
  9. Golle, P., Ducheneaut, N.: Preventing bots from playing online games. Comput. Entertain. 3, 1–10 (2005)Google Scholar
  10. Hu, S.-Y., Liao, G.-M.: Scalable peer-to-peer networked virtual environment. In: Proceedings of 3rd ACM SIGCOMM Workshop on Network and System Support for Games, pp. 129–133 (2004)Google Scholar
  11. Kang, A.R., Kim, H.K., Woo, J.: Chatting pattern based game bot detection: do they talk like us? KSII Trans. Internet Inf. Syst. 6, 2866–2879 (2012)Google Scholar
  12. Kang, A.R., Woo, J., Park, J., Kim, H.K.: Online game bot detection based on party-play log analysis. Comput. Math. Appl. 65, 1384–1395 (2013)CrossRefGoogle Scholar
  13. Keegan, B., Ahmed, M.A., Williams, D., Srivastava, J., Contractor, N.: Dark gold: statistical properties of clandestine networks in massively multiplayer online games, social computing (SocialCom). In: IEEE Second International Conference on, pp. 201–208 (2010)Google Scholar
  14. Keegan, B., Ahmed, M.A., Williams, D., Srivastava, J., Contractor, N.: Sic Transit Gloria Mundi Virtuali?: Promise and peril in the computational social science of clandestine organizing. In: Proceedings of the 3rd International Web Science Conference, vol. 24 (2011)Google Scholar
  15. Kesteren, M., Langevoort, J., Grootjen, F.: A step in the right direction: Bot detection in Mmorpgs using movement analysis. In: Proceedings of the 21st Belgian-Dutch Conference on Artificial Intelligence (2009)Google Scholar
  16. Khanh, Van Nguyen, G.: A Windows-based software architecture for protecting online games against hackers. In: Proceedings of the 2010 Symposium on Information and Communication Technology, pp. 171–178 (2010)Google Scholar
  17. Ki, Y., Woo, J., Kim, H.K.: Identifying spreaders of malicious behaviors in online games. In: Proceedings of the Companion Publication of the 23rd International Conference on World Wide Web Companion, pp. 315–316 (2014)Google Scholar
  18. Kwon, H., Mohaisen, A., Woo, J., Kim, Y., Kim, H.K.: Crime scene reconstruction: online gold-farming network analysis, under review. In: IEEE Transactions on Information Forensics & Security 2015, pp. 1–11 (2015)Google Scholar
  19. Lee, J., Lim, J., Cho, W., Kim, H.K.: In-Game action sequence analysis for game bot detection on the big data analysis platform. In: Proceedings of the 18th Asia Pacific Symposium on Intelligent and Evolutionary Systems, vol. 2, pp. 403–414 (2014)Google Scholar
  20. Mitterhofer, S., Platzer, C., Kruegel, C., Kirda, E.: Server-side bot detection in massive multiplayer online games. IEEE Secur. Priv. 7, 29–36 (2009)CrossRefGoogle Scholar
  21. Oh, J., Borbora, Z.H., Sharma, D., Srivastava, J.: Bot detection based on social interactions in MMORPGs, Social Computing (SocialCom). In: 2013 International Conference on, pp. 536–543 (2013)Google Scholar
  22. Platzer, C.: Sequence-based bot detection in massive multiplayer online games. In: Information, Communications and Signal Processing (ICICS) 2011 8th International Conference on, pp. 1–5 (2011)Google Scholar
  23. Woo, K., Kwon, H., Kim, H.-c., Kim, C.-k., Kim, H.K.: What can free money tell us on the virtual black market? ACM SIGCOMM Comput. Comm. Rev. 41, 392–393 (2011)CrossRefGoogle Scholar
  24. Woo, J., Kim, H. K.: Survey and research direction on online game security. In Proceedings of the Workshop at ACM SIGGRAPH Asia. pp. 19–25 (2012)Google Scholar
  25. Woo, J., Kang, A.R., Kim, H.K.: Modeling of bot usage diffusion across social networks in MMORPGs. In: Proceedings of the Workshop at SIGGRAPH Asia, pp. 13–18 (2013a)Google Scholar
  26. Woo, J., Kang, A.R., Kim, H.K.: The contagion of malicious behaviors in online games. In: Proceedings of the ACM SIGCOMM 2013 Conference on SIGCOMM, pp. 543–544 (2013b)Google Scholar
  27. Yampolskiy, R.V., Govindaraju, V.: Embedded noninteractive continuous bot detection. Comput. Entertain. 5, 7 (2008)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  1. 1.Graduate School of Information SecurityKorea UniversitySeongbuk-GuRepublic of Korea