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Session Name:

Machine Learning Summit: Developing a Stats-Based Anti-Cheat Framework for 'Rainbow Six Siege'

Overview:

Cheating in multiplayer online games negatively impacts player perception and engagement. To address this, a cheater detection system using machine learning driven by in-game player stats was developed for Rainbow Six Siege, operational since early 2024. It robustly identifies players with extremely high in-game performances. This talk covers how to create a labeled dataset to train our model, process data to make it robust against trends and variability, and regularly update and validate our model with the help of moderators. Moving forward, the goal is to establish this as the standard method for all our upcoming competitive FPS games.

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