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Detect Cheater in Online Gaming using AI

Bajaj, Sparsh (2022) Detect Cheater in Online Gaming using AI. Masters thesis, Dublin, National College of Ireland.

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With the increase in popularity, gaming has become one of the major industries, and cheating in video games is also increasingly common nowadays as everyone wants the top spot. Reduced game traffic is usually caused due to the drastic increase in cheaters, and, at the same time, cheats sold online, resulting in the lower income generated for the studios.

Because of the cheaters in the gaming industry, game developers have developed and deployed numerous anti-cheating strategies. Installing an application with kernel-level access to the client's system is mandatory for a few anti-cheat strategies, and most gamers are concerned about their security and privacy in this aspect. A few issues with the OS caused by the anti-cheat software have been documented; the registered users have claimed that the application reportedly leads to upgrades failing.

With machine learning methods and statistical analysis, this study seeks to identify cheaters from players while protecting one's privacy and personal information.

Item Type: Thesis (Masters)
Spelman, Ross
Subjects: Q Science > QA Mathematics > Electronic computers. Computer science
T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science
Q Science > QH Natural history > QH301 Biology > Methods of research. Technique. Experimental biology > Data processing. Bioinformatics > Artificial intelligence
Q Science > Q Science (General) > Self-organizing systems. Conscious automata > Artificial intelligence
Q Science > QA Mathematics > Computer software > Computer Security
T Technology > T Technology (General) > Information Technology > Computer software > Computer Security
G Geography. Anthropology. Recreation > GV Recreation Leisure > Games and Amusements > Online Games
Divisions: School of Computing > Master of Science in Cyber Security
Depositing User: Tamara Malone
Date Deposited: 24 Apr 2023 14:26
Last Modified: 24 Apr 2023 14:26

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