Hard-core user and bot user classification using game character's growth types

Jin Lee, Sung Wook Kang, Huy Kang Kim

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Online game bots unfairly collect items and money, then rapidly deplete the in-game contents. Furthermore, recently game bots have been stealing the gamer's personal information and cause account thefts problems. These problems can have disastrous effects as well as leading to a downturn in the online gaming industry. There have been various countermeasures to detect game bots. However, misclassification between game bots and hard-core users is the well-known problem for a long time. In this paper, we define the growth types by analyzing the growth processes of users with the Aion dataset, one of the famous MMORPGs in the world. We propose a framework that classifies hard-core users and game bots in the growth patterns. As a result, we successfully distinguish game bots from hard-core users with high accuracy value.

Original languageEnglish
Title of host publication2015 International Workshop on Network and Systems Support for Games, NetGames 2015
PublisherIEEE Computer Society
ISBN (Electronic)9781509000685
DOIs
Publication statusPublished - 2016 Jan 13
EventInternational Workshop on Network and Systems Support for Games, NetGames 2015 - Zagreb, Croatia
Duration: 2015 Dec 32015 Dec 4

Publication series

NameAnnual Workshop on Network and Systems Support for Games
Volume2016-January
ISSN (Print)2156-8138
ISSN (Electronic)2156-8146

Other

OtherInternational Workshop on Network and Systems Support for Games, NetGames 2015
Country/TerritoryCroatia
CityZagreb
Period15/12/315/12/4

Keywords

  • Bot detection
  • Hard-core user
  • Massively Multiplayer Online Role-Playing Game
  • User behavior analysis

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Human-Computer Interaction
  • Electrical and Electronic Engineering

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