Multimodal game bot detection using user behavioral characteristics

Ah Reum Kang; Seong Hoon Jeong; Aziz Mohaisen; Huy Kang Kim

doi:10.1186/s40064-016-2122-8

Multimodal game bot detection using user behavioral characteristics

Ah Reum Kang, Seong Hoon Jeong, Aziz Mohaisen, Huy Kang Kim

School of Cybersecurity

Research output: Contribution to journal › Article › peer-review

23 Citations (Scopus)

Abstract

As the online service industry has continued to grow, illegal activities in the online world have drastically increased and become more diverse. Most illegal activities occur continuously because cyber assets, such as game items and cyber money in online games, can be monetized into real currency. The aim of this study is to detect game bots in a massively multiplayer online role playing game (MMORPG). We observed the behavioral characteristics of game bots and found that they execute repetitive tasks associated with gold farming and real money trading. We propose a game bot detection method based on user behavioral characteristics. The method of this paper was applied to real data provided by a major MMORPG company. Detection accuracy rate increased to 96.06 % on the banned account list.

Original language	English
Article number	523
Journal	SpringerPlus
Volume	5
Issue number	1
DOIs	https://doi.org/10.1186/s40064-016-2122-8
Publication status	Published - 2016 Dec 1

Keywords

Behavior analysis
Data mining
MMORPG
Online game security
Social network analysis

ASJC Scopus subject areas

General

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10.1186/s40064-016-2122-8

Cite this

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abstract = "As the online service industry has continued to grow, illegal activities in the online world have drastically increased and become more diverse. Most illegal activities occur continuously because cyber assets, such as game items and cyber money in online games, can be monetized into real currency. The aim of this study is to detect game bots in a massively multiplayer online role playing game (MMORPG). We observed the behavioral characteristics of game bots and found that they execute repetitive tasks associated with gold farming and real money trading. We propose a game bot detection method based on user behavioral characteristics. The method of this paper was applied to real data provided by a major MMORPG company. Detection accuracy rate increased to 96.06 % on the banned account list.",

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AU - Jeong, Seong Hoon

AU - Mohaisen, Aziz

AU - Kim, Huy Kang

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AB - As the online service industry has continued to grow, illegal activities in the online world have drastically increased and become more diverse. Most illegal activities occur continuously because cyber assets, such as game items and cyber money in online games, can be monetized into real currency. The aim of this study is to detect game bots in a massively multiplayer online role playing game (MMORPG). We observed the behavioral characteristics of game bots and found that they execute repetitive tasks associated with gold farming and real money trading. We propose a game bot detection method based on user behavioral characteristics. The method of this paper was applied to real data provided by a major MMORPG company. Detection accuracy rate increased to 96.06 % on the banned account list.

KW - Behavior analysis

KW - Data mining

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KW - Online game security

KW - Social network analysis

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Multimodal game bot detection using user behavioral characteristics

Abstract

Keywords

ASJC Scopus subject areas

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