Ok like, what the actual fuck? How is this ok with any privacy policy? I have never noticed this because any game I played ever showed this menu to me. Is there any way to not let this fucking “anti-cheat” (looks more like a trojan) to steal every single data from my activity?
So how do you propose detecting that a client is rendering a model that shouldn’t be rendered (because it’s behind a solid wall for example) without some client-side anticheat?
Sigh…
Rather than endlessly nitpicking special cases that you assume are unsolvable, I suggest you spend some time reading about the topic. The answers might not be obvious to you, but they do exist.
(And while I would like to believe that you’re genuinely interested, rather than just posturing on the internet, I’ve already spent as much time here as I can spare.)
Wallhacking isn’t a special case…? It’s one of the most common cheats and gives an enormous advantage.
So again, what’s your master method? The server doesn’t send player positions until nearly within the other player’s sight, but even that already gives a huge advantage and is nothing the server can do about it via non-LAN networks, otherwise people will be “popping out” / managing to attack the other player before their position was even received by the player being attacked.
Certain genres of games can work well with only server-side anticheat, but FPS isn’t one of them.
Only send updates of position of the players that are likely to be visible ?
And then you read my previous message about that working very badly due to lag interpretation for example?
The other user didn’t answer your question fully, but heuristic algorithms are very good for this purpose! if you’re able to identify some specific things in players behavior that only occur when they are cheating, you can easily create a machine learning system to identify that behavior, incorporating things like batch punishment (such as VAC or Hypixel’s Watchdog) to make it more difficult for cheat devs to identify the reason, or a manually-reviewed appeal process to account for errors in the model.