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AntiCheatPT: A Transformer-Based Approach to Cheat Detection in Competitive Computer Games

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AntiCheatPT

A machine learning based cheat detection system based on a transformer. The project contains the code used to produce the results reported in the article titled "AntiCheatPT: A Transformer-Based Approach to Cheat Detection in Competitive Computer Games" by Mille Mei Zhen Loo, Gert Luẑkov and Paolo Burelli, published in the proceedings of the 2025 IEEE Conference on Games. The article can be found at https://arxiv.org/pdf/2508.06348 and https://ieeexplore.ieee.org/abstract/document/11114092/?casa_token=j7tlUKwgM0UAAAAA:tXu8N-lbWMaRaK2C3pJJhTRnyD3DXIPjMUNnK5-Gdbhwdm_IoQUY2cCNQtHZz7yQ4YmM590

This project is a fork of the original student's code available at https://github.com/Pinkvinus/CS2_cheat_detection created as a permanent copy.

The data used in the article can be found at https://huggingface.co/datasets/CS2CD/CS2CD.Counter-Strike_2_Cheat_Detection

If you use this code or the data, please cite the article as:

Loo, M. M. Z., Luẑkov, G., & Burelli, P. (2025, August). AntiCheatPT: A Transformer-Based Approach to Cheat Detection in Competitive Computer Games. In 2025 IEEE Conference on Games (CoG) (pp. 1-4). IEEE.

Alternatively, you can use the following bibtex code:

@inproceedings{loo2025anticheatpt, title={AntiCheatPT: A Transformer-Based Approach to Cheat Detection in Competitive Computer Games}, author={Loo, Mille Mei Zhen and Luẑkov, Gert and Burelli, Paolo}, booktitle={2025 IEEE Conference on Games (CoG)}, pages={1--4}, year={2025}, organization={IEEE} }

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