Hard-core user and bot user classification using game character's growth types

Jin Lee; Sung Wook Kang; Huy Kang Kim

doi:10.1109/NetGames.2015.7383000

Hard-core user and bot user classification using game character's growth types

Jin Lee, Sung Wook Kang, Huy Kang Kim

Graduate School of Information Study

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

Abstract

Online game bots unfairly collect items and money, then rapidly deplete the in-game contents. Furthermore, recently game bots have been stealing the gamer's personal information and cause account thefts problems. These problems can have disastrous effects as well as leading to a downturn in the online gaming industry. There have been various countermeasures to detect game bots. However, misclassification between game bots and hard-core users is the well-known problem for a long time. In this paper, we define the growth types by analyzing the growth processes of users with the Aion dataset, one of the famous MMORPGs in the world. We propose a framework that classifies hard-core users and game bots in the growth patterns. As a result, we successfully distinguish game bots from hard-core users with high accuracy value.

Original language	English
Title of host publication	2015 International Workshop on Network and Systems Support for Games, NetGames 2015
Publisher	IEEE Computer Society
ISBN (Electronic)	9781509000685
DOIs	https://doi.org/10.1109/NetGames.2015.7383000
Publication status	Published - 2016 Jan 13
Event	International Workshop on Network and Systems Support for Games, NetGames 2015 - Zagreb, Croatia Duration: 2015 Dec 3 → 2015 Dec 4

Publication series

Name	Annual Workshop on Network and Systems Support for Games
Volume	2016-January
ISSN (Print)	2156-8138
ISSN (Electronic)	2156-8146

Other

Other	International Workshop on Network and Systems Support for Games, NetGames 2015
Country	Croatia
City	Zagreb
Period	15/12/3 → 15/12/4

Keywords

Bot detection
Hard-core user
Massively Multiplayer Online Role-Playing Game
User behavior analysis

ASJC Scopus subject areas

Computer Networks and Communications
Human-Computer Interaction
Electrical and Electronic Engineering

Access to Document

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Hard-core user and bot user classification using game character's growth types. / Lee, Jin; Kang, Sung Wook; Kim, Huy Kang.

2015 International Workshop on Network and Systems Support for Games, NetGames 2015. IEEE Computer Society, 2016. 7383000 (Annual Workshop on Network and Systems Support for Games; Vol. 2016-January).

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

Lee, J, Kang, SW & Kim, HK 2016, Hard-core user and bot user classification using game character's growth types. in 2015 International Workshop on Network and Systems Support for Games, NetGames 2015., 7383000, Annual Workshop on Network and Systems Support for Games, vol. 2016-January, IEEE Computer Society, International Workshop on Network and Systems Support for Games, NetGames 2015, Zagreb, Croatia, 15/12/3. https://doi.org/10.1109/NetGames.2015.7383000

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title = "Hard-core user and bot user classification using game character's growth types",

abstract = "Online game bots unfairly collect items and money, then rapidly deplete the in-game contents. Furthermore, recently game bots have been stealing the gamer's personal information and cause account thefts problems. These problems can have disastrous effects as well as leading to a downturn in the online gaming industry. There have been various countermeasures to detect game bots. However, misclassification between game bots and hard-core users is the well-known problem for a long time. In this paper, we define the growth types by analyzing the growth processes of users with the Aion dataset, one of the famous MMORPGs in the world. We propose a framework that classifies hard-core users and game bots in the growth patterns. As a result, we successfully distinguish game bots from hard-core users with high accuracy value.",

keywords = "Bot detection, Hard-core user, Massively Multiplayer Online Role-Playing Game, User behavior analysis",

author = "Jin Lee and Kang, {Sung Wook} and Kim, {Huy Kang}",

note = "Funding Information: We would like to thank NC Soft, Inc. for providing dataset. This work was supported by the MSIP (Ministry of Science, ICT and Future Planning), Korea Publisher Copyright: {\textcopyright} 2015 IEEE.; International Workshop on Network and Systems Support for Games, NetGames 2015 ; Conference date: 03-12-2015 Through 04-12-2015",

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doi = "10.1109/NetGames.2015.7383000",

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AU - Kang, Sung Wook

AU - Kim, Huy Kang

N1 - Funding Information: We would like to thank NC Soft, Inc. for providing dataset. This work was supported by the MSIP (Ministry of Science, ICT and Future Planning), Korea Publisher Copyright: © 2015 IEEE.

PY - 2016/1/13

Y1 - 2016/1/13

N2 - Online game bots unfairly collect items and money, then rapidly deplete the in-game contents. Furthermore, recently game bots have been stealing the gamer's personal information and cause account thefts problems. These problems can have disastrous effects as well as leading to a downturn in the online gaming industry. There have been various countermeasures to detect game bots. However, misclassification between game bots and hard-core users is the well-known problem for a long time. In this paper, we define the growth types by analyzing the growth processes of users with the Aion dataset, one of the famous MMORPGs in the world. We propose a framework that classifies hard-core users and game bots in the growth patterns. As a result, we successfully distinguish game bots from hard-core users with high accuracy value.

AB - Online game bots unfairly collect items and money, then rapidly deplete the in-game contents. Furthermore, recently game bots have been stealing the gamer's personal information and cause account thefts problems. These problems can have disastrous effects as well as leading to a downturn in the online gaming industry. There have been various countermeasures to detect game bots. However, misclassification between game bots and hard-core users is the well-known problem for a long time. In this paper, we define the growth types by analyzing the growth processes of users with the Aion dataset, one of the famous MMORPGs in the world. We propose a framework that classifies hard-core users and game bots in the growth patterns. As a result, we successfully distinguish game bots from hard-core users with high accuracy value.

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KW - Hard-core user

KW - Massively Multiplayer Online Role-Playing Game

KW - User behavior analysis

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Hard-core user and bot user classification using game character's growth types

Abstract

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Keywords

ASJC Scopus subject areas

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