Detection of auto programs for MMORPGs

Hyungil Kim, Sungwoo Hong, Juntae Kim

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

30 Scopus citations

Abstract

Auto-playing programs are often used on behalf of human players in a MMORPG(Massively Multi-player Online Role Playing Game). By playing automatically and continuously, it helps to speed up the game character's level-up process. However, the auto-playing programs, either software or hardware, do harm to games servers in various ways including abuse of resources. In this paper, we propose a way of detecting the auto programs by analyzing the window event sequences produced by the game players. In our proposed method, the event sequences are transformed into a set of attributes, and various learning algorithms are applied to classify the data represented by the set of attribute values into human or auto player. The results from experiments with several MMORPGs show that the Decision Tree learning with proposed method can identify the auto-playing programs with high accuracy.

Original languageEnglish
Title of host publicationAI 2005
Subtitle of host publicationAdvances in Artificial Intelligence - 18th Australian Joint Conference on Artificial Intelligence, Proceedings
PublisherSpringer Verlag
Pages1281-1284
Number of pages4
ISBN (Print)3540304622, 9783540304623
DOIs
StatePublished - 2005
Event18th Australian Joint Conference on Artificial Intelligence, AI 2005: Advances in Artificial Intelligence - Sydney, Australia
Duration: 5 Dec 20059 Dec 2005

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume3809 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference18th Australian Joint Conference on Artificial Intelligence, AI 2005: Advances in Artificial Intelligence
Country/TerritoryAustralia
CitySydney
Period5/12/059/12/05

Keywords

  • Data Mining
  • Entertainment and AI
  • Intelligent Data Analysis
  • Machine Learning

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