The gravy value: A set of features for pinpointing BOT detection method

Semi Park; Kyungho Lee

doi:10.1007/978-3-030-65299-9_11

The gravy value: A set of features for pinpointing BOT detection method

Semi Park, Kyungho Lee

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

1 Citation (Scopus)

Abstract

The critical success of online games has led the industry to global success, as the market size is expected to reach 18,194 USD by the year 2020. However, the success of the online game market has led to the growth of illegal activities, such as the use of game bots. Game bots are software applications capable of collecting game items, which are often banned from online game service providers. The illegal activities are not limited to tax evasion and money laundering. In order to help detect these bots, this study employs the dataset from an MMORPG called Aion. By detecting the bots using the server-side analysis, this paper analyzed user behavior and used features based on the experience, skill, and gravy value that represents the cost-efficiency. We experimented with machine learning algorithms such as MLP, SVM, and Random Forest. As a result, the F-score for detecting the total sum of the accounts that consists of the game bots and real users reached 0.9638. We believe our study may help online game service providers, future researchers, and governmental agencies to detect and classify the MMORPG game bots.

Original language	English
Title of host publication	Information Security Applications - 21st International Conference, WISA 2020, Revised Selected Papers
Editors	Ilsun You
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	142-153
Number of pages	12
ISBN (Print)	9783030652982
DOIs	https://doi.org/10.1007/978-3-030-65299-9_11
Publication status	Published - 2020
Event	21st International Conference on Information Security Applications, WISA 2020 - Jeju Island, Korea, Republic of Duration: 2020 Aug 26 → 2020 Aug 28

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	12583 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	21st International Conference on Information Security Applications, WISA 2020
Country/Territory	Korea, Republic of
City	Jeju Island
Period	20/8/26 → 20/8/28

Bibliographical note

Publisher Copyright:
© Springer Nature Switzerland AG 2020.

Keywords

BOT detection
MMORPG
Machine learning
Online game
Security

ASJC Scopus subject areas

Theoretical Computer Science
General Computer Science

Access to Document

10.1007/978-3-030-65299-9_11

Cite this

Park, S., & Lee, K. (2020). The gravy value: A set of features for pinpointing BOT detection method. In I. You (Ed.), Information Security Applications - 21st International Conference, WISA 2020, Revised Selected Papers (pp. 142-153). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 12583 LNCS). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-030-65299-9_11

The gravy value: A set of features for pinpointing BOT detection method. / Park, Semi; Lee, Kyungho.
Information Security Applications - 21st International Conference, WISA 2020, Revised Selected Papers. ed. / Ilsun You. Springer Science and Business Media Deutschland GmbH, 2020. p. 142-153 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 12583 LNCS).

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

Park, S & Lee, K 2020, The gravy value: A set of features for pinpointing BOT detection method. in I You (ed.), Information Security Applications - 21st International Conference, WISA 2020, Revised Selected Papers. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 12583 LNCS, Springer Science and Business Media Deutschland GmbH, pp. 142-153, 21st International Conference on Information Security Applications, WISA 2020, Jeju Island, Korea, Republic of, 20/8/26. https://doi.org/10.1007/978-3-030-65299-9_11

Park S, Lee K. The gravy value: A set of features for pinpointing BOT detection method. In You I, editor, Information Security Applications - 21st International Conference, WISA 2020, Revised Selected Papers. Springer Science and Business Media Deutschland GmbH. 2020. p. 142-153. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-030-65299-9_11

Park, Semi ; Lee, Kyungho. / The gravy value : A set of features for pinpointing BOT detection method. Information Security Applications - 21st International Conference, WISA 2020, Revised Selected Papers. editor / Ilsun You. Springer Science and Business Media Deutschland GmbH, 2020. pp. 142-153 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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abstract = "The critical success of online games has led the industry to global success, as the market size is expected to reach 18,194 USD by the year 2020. However, the success of the online game market has led to the growth of illegal activities, such as the use of game bots. Game bots are software applications capable of collecting game items, which are often banned from online game service providers. The illegal activities are not limited to tax evasion and money laundering. In order to help detect these bots, this study employs the dataset from an MMORPG called Aion. By detecting the bots using the server-side analysis, this paper analyzed user behavior and used features based on the experience, skill, and gravy value that represents the cost-efficiency. We experimented with machine learning algorithms such as MLP, SVM, and Random Forest. As a result, the F-score for detecting the total sum of the accounts that consists of the game bots and real users reached 0.9638. We believe our study may help online game service providers, future researchers, and governmental agencies to detect and classify the MMORPG game bots.",

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The gravy value: A set of features for pinpointing BOT detection method

Abstract

Publication series

Conference

Bibliographical note

Keywords

ASJC Scopus subject areas

Access to Document

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