research-article

User identification based on game-play activity patterns

Authors:

Li-Wen HongAuthors Info & Claims

NetGames '07: Proceedings of the 6th ACM SIGCOMM workshop on Network and system support for games

Pages 7 - 12

https://doi.org/10.1145/1326257.1326259

Published: 19 September 2007 Publication History

Abstract

Account hijacking is considered one of the most serious security problems in online games. A hijacker normally takes away valuable virtual items from the stolen accounts, and trades those items for real money. Even though account hijacking is not uncommon, there is currently no general solutions to determine whether an account has been hijacked. The game company is not aware of a hijack unless it is reported by the victim. However, it is usually too late---usually a hijacker already took away anything valuable when a user finds that his/her account has been stolen.

In this paper, we propose a new biometric for human identification based on users' game-play activities. Our main summary are two-fold: 1) we show that the idle time distribution is a representative feature of game players; 2) we propose the RET scheme, which is based on the KullbackLeibler divergence between idle time distributions, for user identification. Our evaluations shows that the RET scheme achieves higher than 90% accuracy with a 20-minute detection time given a 200-minute history size.

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Cited By

Kang YKim H(2022)Quick and easy game bot detection based on action time interval estimationETRI Journal10.4218/etrij.2022-0089Online publication date: 4-Dec-2022
https://doi.org/10.4218/etrij.2022-0089
Yu HHarper SVigo MBellogin ABoratto LSantos OArdissono LKnijnenburg B(2022)Low-Level Activity Patterns as Indicators of User Familiarity with WebsitesProceedings of the 30th ACM Conference on User Modeling, Adaptation and Personalization10.1145/3503252.3531300(153-163)Online publication date: 4-Jul-2022
https://dl.acm.org/doi/10.1145/3503252.3531300
Kim HLee SWoo JKim H(2022)Justice League: Time-series Game Player Pattern Detection to Discover Rank-Skill Mismatch2022 IEEE International Conference on Agents (ICA)10.1109/ICA55837.2022.00014(42-47)Online publication date: Nov-2022
https://doi.org/10.1109/ICA55837.2022.00014
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User identification based on game-play activity patterns

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cover image ACM Conferences

NetGames '07: Proceedings of the 6th ACM SIGCOMM workshop on Network and system support for games

September 2007

138 pages

ISBN:9780980446005

DOI:10.1145/1326257

Conference Chair:
Grenville Armitage
Swinburne University of Technology, Australia

Copyright © 2007 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Publication History

Published: 19 September 2007

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National Science Council Taiwan

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NetGames07

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ACM

NetGames07: 6th Annual Workshop on Network Systems Support for Games

September 19 - 20, 2007

Melbourne, Australia

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https://doi.org/10.4218/etrij.2022-0089
Yu HHarper SVigo MBellogin ABoratto LSantos OArdissono LKnijnenburg B(2022)Low-Level Activity Patterns as Indicators of User Familiarity with WebsitesProceedings of the 30th ACM Conference on User Modeling, Adaptation and Personalization10.1145/3503252.3531300(153-163)Online publication date: 4-Jul-2022
https://dl.acm.org/doi/10.1145/3503252.3531300
Kim HLee SWoo JKim H(2022)Justice League: Time-series Game Player Pattern Detection to Discover Rank-Skill Mismatch2022 IEEE International Conference on Agents (ICA)10.1109/ICA55837.2022.00014(42-47)Online publication date: Nov-2022
https://doi.org/10.1109/ICA55837.2022.00014
Han MKwak BKim H(2022)Cheating and Detection Method in Massively Multiplayer Online Role-Playing Game: Systematic Literature ReviewIEEE Access10.1109/ACCESS.2022.317211010(49050-49063)Online publication date: 2022
https://doi.org/10.1109/ACCESS.2022.3172110
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Kim CKim H(2020)Identification of the Use of Unauthorized Apps in the O2O Service by Combining Online Events and Offline ConditionsElectronics10.3390/electronics91119779:11(1977)Online publication date: 22-Nov-2020
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Park SLee K(2020)The Gravy Value: A Set of Features for Pinpointing BOT Detection MethodInformation Security Applications10.1007/978-3-030-65299-9_11(142-153)Online publication date: 9-Dec-2020
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