General research focused on identifying, detecting, or preventing cheating behaviors.
This dossier summarizes the cheat definition, the affected OSI layer, and the evidence attached to the record.
General research focused on identifying, detecting, or preventing cheating behaviors.
Layer 7 (Application)
General research focused on identifying, detecting, or preventing cheating behaviors.
Peer-reviewed and academic literature connected to this cheat, with DOI or URL references attached where available.
Aditya Jonnalagadda, Iuri Frosio, Seth Schneider, Morgan McGuire, Joohwan Kim
Proceedings of the ACM on Computer Graphics and Interactive Techniques, Vol. 4, No. 1, 2021
Target: Visual hacks, wallhacks, aimbot assistance, extrasensory perception cheats
Aim: Jonnalagadda, A., Frosio, I., Schneider, S., McGuire, M., & Kim, J. (2021). Robust vision-based cheat detection in competitive gaming. Proceedings of the ACM on Computer Graphics and Interactive Techniques, 4(1), Article 7.
Recommendation: (Jonnalagadda et al., 2021)
No external DOI or URL link is attached yet.
Qinghao Zhang
2021 2nd International Conference on Information Science and Education (ICISE-IE)
Target: Packet cheating (server deception), RAM cheating (memory modification), traditional anti-cheat system limitations
Aim: Zhang, Q. (2021). Improvement of online game anti-cheat system based on deep learning. In 2021 2nd International Conference on Information Science and Education (ICISE-IE) (pp. 652-655). IEEE.
Recommendation: (Zhang, 2021)
No external DOI or URL link is attached yet.
Reviewed white papers and adjacent technical reports approved for this dossier.
Reviewed non-academic sources such as news, forums, archives, or enforcement materials.
Named incidents, documented examples, or sanctions associated with this cheat category.