Online game bot detection based on party-play log analysis

Ah Reum Kang, Jiyoung Woo, Juyong Park, Huy Kang Kim

Research output: Contribution to journalArticle

45 Citations (Scopus)

Abstract

As online games become popular and the boundary between virtual and real economies blurs, cheating in games has proliferated in volume and method. In this paper, we propose a framework for user behavior analysis for bot detection in online games. Specifically, we focus on party play which reflects the social activities among gamers: in a Massively Multi-user Online Role Playing Game (MMORPG), party play is a major activity that game bots exploit to keep their characters safe and facilitate the acquisition of cyber assets in a fashion very different from that of normal humans. Through a comprehensive statistical analysis of user behaviors in game activity logs, we establish threshold levels for the activities that allow us to identify game bots. Based on this, we also build a knowledge base of detection rules, which are generic. We apply our rule reasoner to AION, a popular online game serviced by NCsoft, Inc., a leading online game company based in Korea.

Original languageEnglish
Pages (from-to)1384-1395
Number of pages12
JournalComputers and Mathematics with Applications
Volume65
Issue number9
DOIs
Publication statusPublished - 2013 May

Keywords

  • Game bot
  • MMORPG
  • Online game security
  • User behavior analysis

ASJC Scopus subject areas

  • Modelling and Simulation
  • Computational Theory and Mathematics
  • Computational Mathematics

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