Crime Scene Reconstruction: Online Gold Farming Network Analysis
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Kwon, Hyukmin | - |
dc.contributor.author | Mohaisen, Aziz | - |
dc.contributor.author | Woo, Jiyoung | - |
dc.contributor.author | Kim, Yongdae | - |
dc.contributor.author | Lee, Eunjo | - |
dc.contributor.author | Kim, Huy Kang | - |
dc.date.accessioned | 2021-09-03T09:10:32Z | - |
dc.date.available | 2021-09-03T09:10:32Z | - |
dc.date.created | 2021-06-16 | - |
dc.date.issued | 2017-03 | - |
dc.identifier.issn | 1556-6013 | - |
dc.identifier.uri | https://scholar.korea.ac.kr/handle/2021.sw.korea/84348 | - |
dc.description.abstract | Many online games have their own ecosystems, where players can purchase in-game assets using game money. Players can obtain game money through active participation or "real money trading" through official channels: converting real money into game money. The unofficial market for real money trading gave rise to gold farming groups (GFGs), a phenomenon with serious impact in the cyber and real worlds. GFGs in massively multiplayer online role-playing games (MMORPGs) are some of the most interesting underground cyber economies because of the massive nature of the game. To detect GFGs, there have been various studies using behavioral traits. However, they can only detect gold farmers, not entire GFGs with internal hierarchies. Even worse, GFGs continuously develop techniques to hide, such as forming front organizations, concealing cyber-money, and changing trade patterns when online game service providers ban GFGs. In this paper, we analyze the characteristics of the ecosystem of a large-scale MMORPG, and devise a method for detecting GFGs. We build a graph that characterizes virtual economy transactions, and trace abnormal trades and activities. We derive features from the trading graph and physical networks used by GFGs to identify them in their entirety. Using their structure, we provide recommendations to defend effectively against GFGs while not affecting the existing virtual ecosystem. | - |
dc.language | English | - |
dc.language.iso | en | - |
dc.publisher | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC | - |
dc.subject | BOT DETECTION | - |
dc.title | Crime Scene Reconstruction: Online Gold Farming Network Analysis | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | Kim, Huy Kang | - |
dc.identifier.doi | 10.1109/TIFS.2016.2623586 | - |
dc.identifier.scopusid | 2-s2.0-85007042372 | - |
dc.identifier.wosid | 000391453000004 | - |
dc.identifier.bibliographicCitation | IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY, v.12, no.3, pp.544 - 556 | - |
dc.relation.isPartOf | IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY | - |
dc.citation.title | IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY | - |
dc.citation.volume | 12 | - |
dc.citation.number | 3 | - |
dc.citation.startPage | 544 | - |
dc.citation.endPage | 556 | - |
dc.type.rims | ART | - |
dc.type.docType | Article | - |
dc.description.journalClass | 1 | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Computer Science | - |
dc.relation.journalResearchArea | Engineering | - |
dc.relation.journalWebOfScienceCategory | Computer Science, Theory & Methods | - |
dc.relation.journalWebOfScienceCategory | Engineering, Electrical & Electronic | - |
dc.subject.keywordPlus | BOT DETECTION | - |
dc.subject.keywordAuthor | Online games | - |
dc.subject.keywordAuthor | game bot | - |
dc.subject.keywordAuthor | gold farming group | - |
dc.subject.keywordAuthor | MMORPG | - |
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