Multimodal game bot detection using user behavioral characteristics

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

Research output: Contribution to journalArticle

6 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 languageEnglish
Article number523
JournalSpringerPlus
Volume5
Issue number1
DOIs
Publication statusPublished - 2016 Dec 1

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Industry
Gold

Keywords

  • Behavior analysis
  • Data mining
  • MMORPG
  • Online game security
  • Social network analysis

ASJC Scopus subject areas

  • General

Cite this

Multimodal game bot detection using user behavioral characteristics. / Kang, Ah Reum; Jeong, Seong Hoon; Mohaisen, Aziz; Kim, Huy Kang.

In: SpringerPlus, Vol. 5, No. 1, 523, 01.12.2016.

Research output: Contribution to journalArticle

Kang, Ah Reum ; Jeong, Seong Hoon ; Mohaisen, Aziz ; Kim, Huy Kang. / Multimodal game bot detection using user behavioral characteristics. In: SpringerPlus. 2016 ; Vol. 5, No. 1.
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