this post was submitted on 02 Jan 2026
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[–] Agent_Karyo@piefed.world 7 points 18 hours ago* (last edited 11 hours ago) (1 children)

kernel anti-cheats do not want to develop for Linux due to the lack of a fully secure environment in the OS.

I don't think it will be possible to limit non-casual cheating (i.e. those who are willing to spend money) using the dynamic matchmaking approach.

The only way to beat cheating is to have "old style" community servers with regulars for cheaters to be kickbanned by someone with admin rights and/or server votes for kickbans. Not saying this will happen any time soon in the mainstream, but I don't see an automated approach working short of something like required real world IDs.

[–] SalamenceFury@lemmy.world 2 points 11 hours ago (1 children)

Automated could work using AI to check how someone is playing, since a lot of LLMs are specialized in analyzing if something has human behaviors on it or not, but even then that approach isn't 100% guaranteed. Ideally we'd use server-side anti-cheat instead of offloading it to client side, but that costs money and suits are allergic to spending money.

[–] definitemaybe@lemmy.ca 1 points 1 hour ago

You mean machine learning algorithms (or just "AI"), not Large Language Models. LLMs are just advanced word prediction machines; they're categorically incapable of detecting cheating in a game.

But, yeah. It would totally make sense to have server-side detection for things like:

  • Consistency with performance (no changes over time within or sessions with reaction time, for example)
  • Behaviour changes depending whether there is vs. isn't someone around a corner, particularly in areas with long sight lines so footstep sounds wouldn't trigger
  • Inhumanly quick reaction times, with consistency (e.g. < 100ms reaction times — 101 ms is the world record)

etc.

Sure, people could still have cheats help tweak inputs, a bit, like "gentle" headshot aiming assistance, but it would catch egregious cheaters.