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Game-bot Detection based on Analysis of Harvest Coordinate

  • Journal of The Korea Society of Computer and Information
  • Abbr : JKSCI
  • 2022, 27(5), pp.157-163
  • DOI : 10.9708/jksci.2022.27.05.157
  • Publisher : The Korean Society Of Computer And Information
  • Research Area : Engineering > Computer Science
  • Received : March 18, 2022
  • Accepted : April 25, 2022
  • Published : May 31, 2022

최재웅 1,  Ah Reum Kang 2

1
2배재대학교

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ABSTRACT

As the online game market grows, the use of game bots is causing the most serious problem for game services. We propose a harvest coordinate analysis model to detect harvesting bots among game bots of the Massively Multiplayer Online Role-Playing Games(MMORPGs) genre. The proposed model analyzes the player's harvesting behavior using the coordinate data. Game bots can obtain in-game goods and items more easily than normal players and are not affected by realistic restrictions such as sleep time and character manipulation fatigue. As a result, there is a difference in harvesting coordinates between normal players and game bots. We divided the coordinate zones and used these coordinate zone differences to distinguish between game bot players and normal players. We created a dataset with NCSoft's AION log and applied it to a random forest model to detect game bots, and as a result, we derived performance with a recall of 0.72 and a precision of 0.92.

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* References for papers published after 2023 are currently being built.

This paper was written with support from the National Research Foundation of Korea.
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