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dc.contributor.authorKarkallis, Panicos
dc.contributor.authorBlasco, Jorge
dc.contributor.authorSuarez-Tangil, Guillermo 
dc.contributor.authorPastrana, Sergio
dc.date.accessioned2021-09-23T16:22:27Z
dc.date.available2021-09-23T16:22:27Z
dc.date.issued2021-10
dc.identifier.urihttp://hdl.handle.net/20.500.12761/1514
dc.description.abstractVideogamecheatsdestroytheonlineplayexperienceofusers and result in financial losses for game developers. Similar to hacking communities, cheat developers often organize themselves around forums where they share game cheats and know-how. In this paper, we perform a large-scale measurement of two online forums, MPGH and UnknownCheats, devoted to video game cheating that are nowadays very active and altogether have more than 7 million posts. Video game cheats often require an auxiliary tool to access the victim process, i.e., an injector. This is a type of program that manipulates the game program memory, and it is a key piece for evading cheat detection on the client-side. We leverage the output of our measurement study to build a machine learn- ing classifier that identifies injectors based on their behavioral traits. Our system will help game developers and the anti-cheat industry to identify attack vectors more quickly and will reduce the barriers to study this topic within the academic community.es
dc.language.isoenges
dc.titleDetecting video-game injectors exchanged in game cheating communitieses
dc.typeconference objectes
dc.conference.date4-8 October 2021es
dc.conference.titleEuropean Symposium On Research In Computer Security*
dc.event.typeconferencees
dc.pres.typepaperes
dc.type.hasVersionCVoRes
dc.rights.accessRightsopen accesses
dc.acronymESORICS*
dc.rankA*
dc.description.refereedTRUEes
dc.description.statusinpresses


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