DocumentCode
2392894
Title
Dark Gold: Statistical Properties of Clandestine Networks in Massively Multiplayer Online Games
Author
Keegan, Brian ; Ahmed, Muhammad Aurangzeb ; Williams, Dmitri ; Srivastava, Jaideep ; Contractor, Noshir
Author_Institution
Sch. of Commun., Northwestern Univ., Evanston, IL, USA
fYear
2010
fDate
20-22 Aug. 2010
Firstpage
201
Lastpage
208
Abstract
Gold farming is a set of illicit practices in which players in massively multiplayer online games gather and distribute virtual goods for real money. Using anonymized data from a popular online game to construct networks of characters involved in gold farming, we examine the trade networks of gold farmers, their trading affiliates, and uninvolved characters at large. Our analysis of these complex networks´ connectivity, assortativity, and attack tolerance indicate that farmers exhibit distinctive behavioral signatures which are masked by brokering affiliates. Our findings are compared against a real world drug trafficking network and suggest similarities in both organizations´ network structures which reflect similar effects of secrecy, resilience, and efficiency.
Keywords
computer games; security of data; social aspects of automation; statistical analysis; attack tolerance; behavioral signatures; clandestine networks; dark gold; drug trafficking network; massively multiplayer online games; virtual goods; Databases; Drugs; Games; Gold; Organizations; Resilience; Security; EverQuest 2; MMOG; MMORPG; assortativity; attack tolerance; cybercrime; dark networks; deviance; gold farming; network analysis; online games; real money trade; scale-free;
fLanguage
English
Publisher
ieee
Conference_Titel
Social Computing (SocialCom), 2010 IEEE Second International Conference on
Conference_Location
Minneapolis, MN
Print_ISBN
978-1-4244-8439-3
Electronic_ISBN
978-0-7695-4211-9
Type
conf
DOI
10.1109/SocialCom.2010.36
Filename
5590455
Link To Document