RICOCHET: Anti-Cheat Progress Report – Launch Readiness, Machine Learning and New Features
Combining everything #TeamRICOCHET has developed over the course of the last three years with new Machine Learning advancements, RICOCHET: Anti-Cheat™ is preparing for the launch of Call of Duty®: Modern Warfare® III with a stronger and faster process to combat cheating.
Machine Learning, in combination with client and server-side systems that continue to evolve and grow, helps advance both the speed and accuracy of our prevention techniques and detection systems.
How Does #TeamRICOCHET Use Machine Learning?
Machine Learning advancements have been integrated into our tech to help with efficiency and speed in prevention, detection, and removal of cheaters. Machine Learning advancements enhance our team’s ability by:
In short, Machine Learning helps us anticipate behavior better and operate with more effectiveness, with our team validating for accuracy.
Machine Learning works in concert with our team, providing information to make account decisions – but Machine Learning systems do not issue bans.
Machine Learning also helps enhance existing tools. One example of how we’re using Machine Learning to accelerate our anti-cheat capabilities is with the Replay tool.
Machine Learning x Replay Investigation Tool
Earlier this year we announced a replay investigation tool that captured gameplay data so it could be converted into video internally, allowing our teams to review player matches for problem behavior. This tool has been beneficial since it launched, but the team wanted to drive toward a new goal: Speed.
On average, a #TeamRICOCHET teammate could review somewhere in the ballpark of 700 replay clips in any given day.
Some clips are easy: the most egregious “rage hacking” is simple to spot, but the Replay Investigation Tool
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