
GDC 2018: John McDonald (Valve) - Using Deep Learning to Combat Cheating in CSGO
About this video
A GDC 2018 talk by Valve's John McDonald on VACNet, a deep learning system that analyzes CS:GO gameplay to detect cheaters. It covers how the model is trained on human-reviewed Overwatch cases and how its output feeds human moderation.
Why it appears in the archive
HN points to it as the definitive example of server-side, behavioral, non-invasive anti-cheat using machine learning, often as a counterpoint to kernel-level anti-cheat.
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From the Hacker News discussion
But you can detect serverside (at least probabilistically) if a user is abusing it to their advantage. Some Valve guy gave a great talk about their cheating detection a while back; I found it incredibly impressive: [VIDEO] (can't comment on their effectiveness these days, haven't played CS in a long time)
Read original comment ↗Valves John McDonald recently gave a talk at Gdc how they use machine learning to combat cheaters in CS:GO. Quite interesting to watch. [VIDEO]
Read original comment ↗If you wanna something more novel, look at this talk from Valve [0] on how they are integrating Deep Learning into their CS:GO cheater detection system (confusingly called Overwatch). It's not used to ban users, but rather to bring suspicious plays into their existing user-reviewed moderation system. In general, this type of human/AI side-by-side feedback loop seems to be very successful, all the way from games to moderating content on the web. [0] [VIDEO]
Read original comment ↗[VIDEO] Watch this! It's about using ML to catch cheaters. I searched youtube to show you this video; I used the search term "cs go machine learning". The first video was actually this: [LINK] Looks like it's using ML to make better aimbots--lol!
Read original comment ↗See the video above. It’s a condensed recap of Valve’s GDC 2018 presentation on VACnet. The actual presentation is worth listening to if you have the time. [VIDEO] I disagree on the statement that developers, publishers, and/or anticheat companies are too incompetent to implement good solutions. They have not been putting serious effort into the problem or else the state of cheating in video games wouldn’t be as bad as it is today.
Read original comment ↗I just watched a presentation about using deep learning to detect cheaters in CounterStrike: Go ( [VIDEO] ) and the question he didn't seem to have an answer for was data poisoning -- what if the cheaters all volunteer to be on the anti-cheater jury? Of course they are cross checking juror reliability ratings and stuff, but it's definitely a treadmill.
Read original comment ↗That's not true at all, though? Source has continued to get changes & upgrades over the years. It has a vulkan backend, the UI system is no longer scaleform but a web-based system called Panorama, a new physics engine called Rubikon that replaced the old Havok engine, etc... They aren't putting out many new games, although they did just release Artifact a couple months ago. But DOTA 2 & CSGO continue to get updates, changes, and improvements. CSGO for example has an entirely new, machine-learning based anti-cheat system called VacNet: [VIDEO] They have tons of talks on GDC of all sorts of really cool stuff they are doing that's related to Source 2 and has nothing to do with Steam.
Read original comment ↗> They also have a neural network setup that constantly scans match logs for cheaters For those wondering what this is referring to, it's a system called VACNet[0] presented at GDC last year. [0] [VIDEO] [1] [LINK]
Read original comment ↗