The gravy value: A set of features for pinpointing BOT detection method

Semi Park, Kyungho Lee

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

1 Citation (Scopus)


The critical success of online games has led the industry to global success, as the market size is expected to reach 18,194 USD by the year 2020. However, the success of the online game market has led to the growth of illegal activities, such as the use of game bots. Game bots are software applications capable of collecting game items, which are often banned from online game service providers. The illegal activities are not limited to tax evasion and money laundering. In order to help detect these bots, this study employs the dataset from an MMORPG called Aion. By detecting the bots using the server-side analysis, this paper analyzed user behavior and used features based on the experience, skill, and gravy value that represents the cost-efficiency. We experimented with machine learning algorithms such as MLP, SVM, and Random Forest. As a result, the F-score for detecting the total sum of the accounts that consists of the game bots and real users reached 0.9638. We believe our study may help online game service providers, future researchers, and governmental agencies to detect and classify the MMORPG game bots.

Original languageEnglish
Title of host publicationInformation Security Applications - 21st International Conference, WISA 2020, Revised Selected Papers
EditorsIlsun You
PublisherSpringer Science and Business Media Deutschland GmbH
Number of pages12
ISBN (Print)9783030652982
Publication statusPublished - 2020
Event21st International Conference on Information Security Applications, WISA 2020 - Jeju Island, Korea, Republic of
Duration: 2020 Aug 262020 Aug 28

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume12583 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference21st International Conference on Information Security Applications, WISA 2020
Country/TerritoryKorea, Republic of
CityJeju Island

Bibliographical note

Publisher Copyright:
© Springer Nature Switzerland AG 2020.


  • BOT detection
  • Machine learning
  • Online game
  • Security

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science


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