Playing video games are meant to be a fun experience but something that has been proven to ruin the experience are cheaters, maybe even more so in events such as tournaments where money is involved. Even if anti-cheating software exists there also exists a research gap in the subject of cheat detection. And regarding cheat detection the question that matters the most is: how do you even detect a player that is using 3rd-party software to gain an unfair advantage in online video games? To find a solution for this problem a systematic literature review was made were data was extracted from articles relevant for the subject and summarised into results. From the results, a few elementary concepts regarding cheat detection are introduced and analysed with comparisons to the problem statement. Finally, five different types of cheat detection are shown that work by analysing objects such as behaviour, game state or memory.
| Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:lnu-84878 |
| Date | January 2019 |
| Creators | Björkskog, Gaston |
| Publisher | Linnéuniversitetet, Institutionen för datavetenskap och medieteknik (DM) |
| Source Sets | DiVA Archive at Upsalla University |
| Language | English |
| Detected Language | English |
| Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
| Format | application/pdf |
| Rights | info:eu-repo/semantics/openAccess |
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