title: Multimodal game bot detection using user behavioral characteristics.
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.
authors.affiliation: Department of Computer Science and Engineering, State University of New York at Buffalo, White Road, Buffalo, NY USA.
authors.forename: Ah Reum
authors.initials: AR
authors.lastname: Kang
authors.affiliation: Graduate School of Information Security, Korea University, Anam-ro, Seoul, Korea.
authors.forename: Seong Hoon
authors.initials: SH
authors.lastname: Jeong
authors.affiliation: Department of Computer Science and Engineering, State University of New York at Buffalo, White Road, Buffalo, NY USA.
authors.forename: Aziz
authors.initials: A
authors.lastname: Mohaisen
authors.affiliation: Graduate School of Information Security, Korea University, Anam-ro, Seoul, Korea.
authors.forename: Huy Kang
authors.initials: HK
authors.lastname: Kim
keywords: Behavior analysis; Data mining; MMORPG; Online game security; Social network analysis