alt Hacker NewsThere is a solution to cheating, but it's not clear how hard it would be to implement.
Cheaters are by definition anomalies, they operate with information regular players do not have. And when they use aimbots they have skills other players don't have.
If you log every single action a player takes server-side and apply machine learning methods it should be possible to identify these anomalies. Anomaly detection is a subfield of machine learning.
It will ultimately prove to be the solution, because only the most clever of cheaters will be able to blend in while still looking like great players. And only the most competently made aimbots will be able to appear like great player skills. In either of those cases the cheating isn't a problem because the victims themselves will never be sure.
There is also another method that the server can employ: Players can be actively probed with game world entities designed for them to react to only if they have cheats. Every such event would add probability weight onto the cheaters. Ultimately, the game world isn't delivered to the client in full so if done well the cheats will not be able to filter. For example: as a potential cheater enters entity broadcast range of a fake entity camping in an invisible corner that only appears to them, their reaction to it is evaluated (mouse movements, strategy shift, etc). Then when it disappears another evaluation can take place (cheats would likely offer mitigations for this part). Over time, cheaters will stand out from the noise, most will likely out themselves very quickly.
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I've been advocating for a statistical honeypot model for a while now. This is a much more robust anti cheat measure than even streaming/LAN gaming provides. If someone figures out a way to obtain access to information they shouldn't have on a regular basis, they will be eventually be found with these techniques. It doesn't matter the exact mechanism of cheating. This even catches the "undetectable" screen scraping mouse robot AI wizard stuff. Any amount of signal integrated over enough time can provide damning evidence.
> With that goal in mind, we released a patch as soon as we understood the method these cheats were using. This patch created a honeypot: a section of data inside the game client that would never be read during normal gameplay, but that could be read by these exploits. Each of the accounts banned today read from this "secret" area in the client, giving us extremely high confidence that every ban was well-deserved.
This is said very often, but doesn't seem to be working out in practice.
Valve has spent a lot of time and money on machine learning models which analyze demo files (all inputs). Yet Counter-Strike is still infested with cheaters. I guess we can speculate that it's just a faulty implementation, but clearly the problem isn't just "throw a ML model at the problem".
Honeypots are used pretty often, sure. They're not enough, though useful.
Behavioral analysis is way harder in practice than it sounds, because most closet cheaters do not give enough signal to stand out, and the clusters are moving pretty fast. The way people play the game always changes. It's not the problem of metric selection as it might appear to an engineer, you need to watch the community dynamics. Currently only humans are able to do that.
In CS2, a huge portion of cheaters can be identified just by the single stat 'time-to-damage'. Cheaters will often be 100ms faster to react than even the fastest pros. Not all cheaters use their advantage in this way, but simply always make perfect choices because they have more information than their opponents.
I disagree with the premise that it doesn't matter as long as users can't tell. Say you're running a Counterstrike tournament with a 10k purse... Integrity matters there. And a smart cheater is running 'stealth' in that situation. Think a basic radar or a verrrrrry light aimbot, etc.
The problem is that traditional cheats (aimbot, wallhack, etc.) give users such a huge edge that they are multiple standard deviations from the norm on key metrics. I agree with you on that and there are anticheats that look for that exact thing.
I've also seen anticheats where flagged users have a session reviewed. EG you review a session with "cheats enabled" and try to determine whether you think the user is cheating. This works decently well in a game like CS where you can be reasonably confident over a larger sample size whether a user is playing corners correctly, etc.
The issue with probing for game world entities is that at some point, you have to resolve it in the client. EG "this is a fake player, store it in memory next to the other player entities but don't render this one on screen." This exact thing has happened in multiple games, and has worked as a temporary solution. End of the day, it ends up being a cat and mouse game. Cheat developers detect this and use the same resolution logic as the game client does. Memory addresses change, etc. and the users are blocked from using it for a few hours or a few days, but the developer patches and boom, off to the races.
These days game hacks are a huge business. Cheats often are offered as a subscription and can rank from anywhere from 10-hundreds of dollars a month. It's big money and some of the larger hack manufacturers are full blown companies which can have tens of thousands of customers. It's a huge business.
I think you're realistically left with two options. Require in-person LAN matches with hardware provided by the tournament which is tamper-resistant. Or run on a system so locked down that cheats don't exist.
Both have their own problems... In-person eliminates most of that risk but it's always possible to exploit. Running on a system which is super locked down (say, the most recent playstation) probably works, until someone has a 0day tucked away that they hoard specifically for their advantage. An unlikely scenario but with the money involved in some esports... Anything is possible.
https://www.documentcloud.org/documents/24698335-la22cv00051...
> Cheaters are by definition anomalies
So are very good players, very bad players, players with weird hardware issues, players who just got one in a million lucky…
When you have enough randomly distributed variables, by the law of big numbers some of them will be anomalous by pure chance. You can't just look at any statistical anomaly and declare it must mean something without investigating further.
In science, looking at a huge number of variables and trying to find one or two statistically significant variables so you can publish a paper is called p hacking. This is why there are so many dubious and often even contradictory "health condition linked to X" articles.