Show Me Your Account: Detecting MMORPG Game Bot Leveraging Financial Analysis with LSTM

Kyung Ho Park; Eunjo Lee; Huy Kang Kim

doi:10.1007/978-3-030-39303-8_1

Show Me Your Account: Detecting MMORPG Game Bot Leveraging Financial Analysis with LSTM

Kyung Ho Park, Eunjo Lee, Huy Kang Kim

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

3 Citations (Scopus)

Abstract

With the rapid growth of MMORPG market, game bot detection has become an essential task for maintaining stable in-game ecosystem. To classify bots from normal users, detection methods are proposed in both game client and server-side. Among various classification methods, data mining method in server-side captured unique characteristics of bots efficiently. For features used in data mining, behavioral and social actions of character are analyzed with numerous algorithms. However, bot developers can evade the previous detection methods by changing bot’s activities continuously. Eventually, overall maintenance cost increases because the selected features need to be updated along with the change of bot’s behavior. To overcome this limitation, we propose improved bot detection method with financial analysis. As bot’s activity absolutely necessitates the change of financial status, analyzing financial fluctuation effectively captures bots as a key feature. We trained and tested model with actual data of Aion, a leading MMORPG in Asia. Leveraging that LSTM efficiently recognizes time-series movement of data, we achieved meaningful detection performance. Further on this model, we expect sustainable bot detection system in the near future.

Original language	English
Title of host publication	Information Security Applications - 20th International Conference, WISA 2019, Revised Selected Papers
Editors	Ilsun You
Publisher	Springer
Pages	3-13
Number of pages	11
ISBN (Print)	9783030393021
DOIs	https://doi.org/10.1007/978-3-030-39303-8_1
Publication status	Published - 2020
Event	20th World Conference on Information Security Applications, WISA 2019 - Jeju Island, Korea, Republic of Duration: 2019 Aug 21 → 2019 Aug 24

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	11897 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	20th World Conference on Information Security Applications, WISA 2019
Country/Territory	Korea, Republic of
City	Jeju Island
Period	19/8/21 → 19/8/24

Bibliographical note

Publisher Copyright:
© 2020, Springer Nature Switzerland AG.

Keywords

Game bot detection
LSTM neural networks
MMORPG

ASJC Scopus subject areas

Theoretical Computer Science
General Computer Science

Access to Document

10.1007/978-3-030-39303-8_1

Cite this

Park, K. H., Lee, E., & Kim, H. K. (2020). Show Me Your Account: Detecting MMORPG Game Bot Leveraging Financial Analysis with LSTM. In I. You (Ed.), Information Security Applications - 20th International Conference, WISA 2019, Revised Selected Papers (pp. 3-13). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11897 LNCS). Springer. https://doi.org/10.1007/978-3-030-39303-8_1

Show Me Your Account: Detecting MMORPG Game Bot Leveraging Financial Analysis with LSTM. / Park, Kyung Ho; Lee, Eunjo; Kim, Huy Kang.
Information Security Applications - 20th International Conference, WISA 2019, Revised Selected Papers. ed. / Ilsun You. Springer, 2020. p. 3-13 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11897 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Park, KH, Lee, E & Kim, HK 2020, Show Me Your Account: Detecting MMORPG Game Bot Leveraging Financial Analysis with LSTM. in I You (ed.), Information Security Applications - 20th International Conference, WISA 2019, Revised Selected Papers. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 11897 LNCS, Springer, pp. 3-13, 20th World Conference on Information Security Applications, WISA 2019, Jeju Island, Korea, Republic of, 19/8/21. https://doi.org/10.1007/978-3-030-39303-8_1

Park KH, Lee E, Kim HK. Show Me Your Account: Detecting MMORPG Game Bot Leveraging Financial Analysis with LSTM. In You I, editor, Information Security Applications - 20th International Conference, WISA 2019, Revised Selected Papers. Springer. 2020. p. 3-13. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-030-39303-8_1

Park, Kyung Ho ; Lee, Eunjo ; Kim, Huy Kang. / Show Me Your Account : Detecting MMORPG Game Bot Leveraging Financial Analysis with LSTM. Information Security Applications - 20th International Conference, WISA 2019, Revised Selected Papers. editor / Ilsun You. Springer, 2020. pp. 3-13 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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abstract = "With the rapid growth of MMORPG market, game bot detection has become an essential task for maintaining stable in-game ecosystem. To classify bots from normal users, detection methods are proposed in both game client and server-side. Among various classification methods, data mining method in server-side captured unique characteristics of bots efficiently. For features used in data mining, behavioral and social actions of character are analyzed with numerous algorithms. However, bot developers can evade the previous detection methods by changing bot{\textquoteright}s activities continuously. Eventually, overall maintenance cost increases because the selected features need to be updated along with the change of bot{\textquoteright}s behavior. To overcome this limitation, we propose improved bot detection method with financial analysis. As bot{\textquoteright}s activity absolutely necessitates the change of financial status, analyzing financial fluctuation effectively captures bots as a key feature. We trained and tested model with actual data of Aion, a leading MMORPG in Asia. Leveraging that LSTM efficiently recognizes time-series movement of data, we achieved meaningful detection performance. Further on this model, we expect sustainable bot detection system in the near future.",

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Show Me Your Account: Detecting MMORPG Game Bot Leveraging Financial Analysis with LSTM

Abstract

Publication series

Conference

Bibliographical note

Keywords

ASJC Scopus subject areas

Access to Document

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