Journal of Korea Game Society (한국게임학회 논문지)

Korea Game Society (한국게임학회)
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A Study of Cheater Detection in FPS Game by using User Log Analysis

사용자 로그 분석을 통한 FPS 게임에서의 치팅 사용자 탐지 연구: 인공 신경망 알고리즘을 중심으로

  • Park, Jung Kyu (Graduate School of Information Security, Korea University) ;
  • Han, Mee Lan (Graduate School of Information Security, Korea University) ;
  • Kim, Huy Kang (Graduate School of Information Security, Korea University)
  • 박정규 (고려대학교 정보보호대학원) ;
  • 한미란 (고려대학교 정보보호대학원) ;
  • 김휘강 (고려대학교 정보보호대학원)
  • Received : 2015.04.20
  • Accepted : 2015.04.29
  • Published : 2015.06.20
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Abstract

In-game cheating by the use of unauthorized software programs has always been a big problem that they can damage in First Person Shooting games, although companies operate a variety of client security solutions in order to prevent games from the cheating attempts. This paper proposes a method for detecting cheaters in FPS games by using game log analysis in a server-side. To accomplish this, we did a comparative analysis of characteristics between cheaters and general users focused on commonly loaded logs in the game. We proposed a cheating detection model by using artificial neural network algorithm. In addition, we did the performance evaluation of the proposed model by using the real dataset used in business.

온라인 게임의 인기 장르인 FPS (First Person Shooting) 게임에서 치팅(cheating)을 근절하기 위해 게임 회사는 다양한 클라이언트 보안 솔루션을 운영하고 있지만 불법 프로그램을 이용한 치팅은 끊이지 않고 있으며 이로 인한 피해도 지속적으로 발생하고 있다. 본 논문에서는 서버 단에서 게임 로그 분석을 통해 FPS 게임의 치팅 사용자를 탐지하는 방법을 제안한다. FPS 게임에서 일반적으로 적재되는 로그를 중심으로 치팅 사용자와 일반 사용자의 특성을 비교 분석하고 인공 신경망 알고리즘을 이용해 치팅 사용자를 탐지하는 모델을 생성하였다. 또한 실제 서비스 중인 FPS 게임 로그를 이용해 치팅 사용자 탐지 모델에 대한 성능 평가를 수행하였다.

Keywords

References

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