행위 시간 간격 기반 게임 봇 탐지 기법
Game Bot Detection Based on Action Time Interval
0
조회
0
다운로드
3
인용
0
참고문헌
키워드
초록
온라인 게임 이용자가 증가하고 시장 규모가 커지면서 여러 가지 부정행위가 발생하고 있다. 게임 봇은 플레이 시간을 확보하고, 계정 레벨업과 각종 재화 획득을 용이하게 해주는 대표적인 불법 프로그램이다. 본 연구에서는 이용자의 행위 시간 간격(ATI)을 기반으로 게임 봇을 탐지하는 기법을 제안한다. 이 기법은 게임에서 봇의 행위를 관찰하여 빈도수가 많은 행위를 선별한다. 선별된 행위별로 빈도수, ATI 평균, ATI 표준편차를 feature로 MachineLearning을 적용하여 정상 사용자와 게임 봇을 구분한다. 제안한 기법의 유효성을 검증하기 위해 ‘아이온’ 게임의실제 로그를 이용하여 성능을 측정하였고, 97%의 정확도를 보였다. 이 방법은 캐릭터의 움직임, 소셜 행위 뿐 아니라 이용자의 모든 행위를 이용할 수 있으므로 다양한 게임에 적용할 수 있다.
Abstract
As the number of online game users increases and the market size grows, various kinds of cheating are occurring. Gamebots are a typical illegal program that ensures playtime and facilitates account leveling and acquisition of various goods. Inthis study, we propose a method to detect game bots based on user action time interval (ATI). This technique observes thebehavior of the bot in the game and selects the most frequent actions. We distinguish between normal users and game botsby applying Machine Learning to feature frequency, ATI average, and ATI standard deviation for each selected action. Inorder to verify the effectiveness of the proposed technique, we measured the performance using the actual log of the 'Aion'game and showed an accuracy of 97%. This method can be applied to various games because it can utilize all actions ofusers as well as character movements and social actions.
참고문헌 (22)
- A. Fujita, "Detecting Real Money Traders in MMORPG by Using Trading Network", AIIDE’11, pp.26~31 (2011)
- "Effects of botting on world of warcraft"[URL]
- Jiyoung Woo, "Research Trend of Detection of Cheating in Online games", REVIEW OF KIISC, 27(4), pp.14~21 (2017)
- R. Thawonmas, "Detection of MMORPG Bots based on Behavior Analysis", ACE’08, pp.91~94 (2008)
- K. -T. Chen, "Game Bot Detection Based on Avatar Trajectory", ICEC’08, 5309, pp.94~105 (2009)
- M. van Kesteren, "A Step in the Right Detecting : Bot Detection in MMORPG using Movement Analysis", The 21st Benelux Conference on Artificial Intelligence (2009)
- S. Mitterhofer, "Server-side Bot Detection in Massively Multiplayer Online Games", IEEE Security &Privacy, 7(3), pp.29~36 (2009)
- Kuan-Ta Chen, "User identification based on game-play activity patterns", ACM SIGCOMM workshop on Network and system support for games, pp.7~12 (2007)
- Jina Lee, "I know what the BOTs did yesterday : Full action sequence analysis using Naïve Bayesian algorithm", Annual Workshop on Network and Systems Support for Games, pp.1~2 (2013)
- Eunjo Lee, "You are a Game Bot!:Uncovering Game Bots in MMORPGs via Self-similarity in the Wild" (2016), NDSS
- M. A. Ahmad, "Mining for Gold Farmers : Automatic Detection of Deviant Players in MMOGs", International Conference on Computational Science and Engineering, 4, pp.340~345 (2009)
- Ah Reum Kang, "Online game bot detection based on party-play log analysis", Computers &Mathematics with Applications, 65(9), pp.1384~1395 (2013)
- Y. Chung, "Game Bot Detection Approach Based on Behavior Analysis and Consideration of Various Play Style", Journal of ETRI, 35(6), pp.1058~1067 (2013)
- B. Keegan, "Dark Gold : Statistical Properties of Clandestine Networks in Massively Multiplayer Online Games", IEEE Second International Conference on Social Computing, pp.201~208 (2010)
- J. Woo, "The Contagion of Malicious Behaviors in Online Game", Computer Communication Review, 43, pp.543~544 (2013)
- H. Kwon, "Crime Scene Reconstruction : Online Gold Farming Network Analysis", IEEE Transactions on Information Forensics and Security, 12(3), pp.544~556 (2016)
- 강아름, "Chatting Pattern Based Game BOT Detection: Do They Talk Like Us?", KSII Transactions on Internet and Information Systems, 6(11), pp.2866~2879 (2012), 한국인터넷정보학회
- 이재혁, "모티베이션 이론을 이용한 온라인 게임 내 부정행위 탐지", 한국게임학회 논문지, 15(4), pp.69~78 (2015), 한국게임학회[DOI]
- Ah Reum Kang, "Multimodal game bot detection using user behavioral characteristics", SpringerPlus, 5(1), pp.523~ (2016)