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Multimodal game bot detection using user behavioral characteristics.
Kang, Ah Reum; Jeong, Seong Hoon; Mohaisen, Aziz; Kim, Huy Kang.
Affiliation
  • Kang AR; Department of Computer Science and Engineering, State University of New York at Buffalo, White Road, Buffalo, NY USA.
  • Jeong SH; Graduate School of Information Security, Korea University, Anam-ro, Seoul, Korea.
  • Mohaisen A; Department of Computer Science and Engineering, State University of New York at Buffalo, White Road, Buffalo, NY USA.
  • Kim HK; Graduate School of Information Security, Korea University, Anam-ro, Seoul, Korea.
Springerplus ; 5: 523, 2016.
Article in En | MEDLINE | ID: mdl-27186487
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.
Key words

Full text: 1 Collection: 01-internacional Database: MEDLINE Type of study: Diagnostic_studies Language: En Journal: Springerplus Year: 2016 Document type: Article Country of publication: Switzerland

Full text: 1 Collection: 01-internacional Database: MEDLINE Type of study: Diagnostic_studies Language: En Journal: Springerplus Year: 2016 Document type: Article Country of publication: Switzerland