[IPTN]

You should be able to limit analysis for this type of detection to only the input leading up to a kill/hit and ignoring everything else. The majority of the time players are not shooting could be used to do the analysis with plenty of time to boot midway in a round let alone a full game.

Also simple analysis of only the input streams as you stated really doesn't have to do with the phys rate of the game server and should be alot cheaper computationally. It can be offloaded to another process even if it was found to be too impactful to run alongside the game server directly. Something all those extra cores might be good for.

[Xss3]

Cheats nowadays can and do

a) run on 2nd pc passively capturing the screen and commands to a fake mouse device plugged into both machines,

b) "humanise" the aim with ai models trained on professional players

c) add random variances within the limits of human reaction times

So it doesn't solve things, really it'd still be playing catchup.

[IPTN]

And I'm not refuting that. I was just pointing out a solution to a problem the GP proposed as intractable when trying to analyze player input data streams for cheating. The points you made are valid as far as the evolution of this cat and mouse game is progressing (probably still closer to the end end of can then do for now).

That being said, the vast majority of cheats are not that sophisticated. "Simple" analysis of player input should still be used to make low effort cheats less or ineffective. Especially if used to compare consistency of mechanical play by a player. I doubt most cheaters want to just turn on a full bot that plays by itself for the whole game. You can build a model of play customized for an individual player to look for changes in mechanical skill during critical plays. Then even if that was incorporated into the cheat client so that its 'actions' can't be definitevly detected against the players baseline, it would at least be limited to cheating as that player always playing like it's their best day. Either that or the cheater would have to go fully hands off for that account which I imagine is not as appealing for most cheaters.

Input analysis, even much simpleler approaches, can still be a valuable tool to make cheating more difficult and less opportunistic. The goal would be to raise the barrier of entry to cheating without immediately getting banned beyond downloading and running a client. If people who consider cheating in a game have to: order, wait for, and setup additional hardware then aquire models trained for the latest version of the game that are also trained on pro play in a way that lets the cheating be humanly plausible to remain undetected; it will reduce the total number of people who cheat in that title. Will needing to aquire additional hardware stop all cheating? No, I had a friend as a kid that owned a GameShark that I used and ended up corrupting the save on one of my Pokemon games. But if all of that is what is required to be able to successfully and consistently cheat, it will raise both the cost of development of cheats as well as their price to cheaters.

For top level professional play, in person tournaments on managed setups will remain the gold standard for the forseeable future (and besides they are attractive as events for their own sake). And for the rest of us, we will continue to be trapped in the labyrinth with both the cat and the mice.