Machine Learning Aimbot Detection in Call of Duty

As cheat developers evolve, so must detection techniques. This session will explore our methodologies, challenges and future directions, demonstrating how machine learning is transforming anti-cheat strategies and preserving competitive integrity in online gaming and how Databricks is enabling us to do so.

As online gaming grows, maintaining fair play is an ongoing challenge. Call of Duty, a highly competitive first-person action game, faces aimbot usage—cheats that enable near-perfect accuracy, undermining fair play. Additionally, traditional detection methods are increasingly becoming less effective against advanced cheats that mimic human behavior.

Machine learning presents a scalable and adaptive solution to this. We developed a data pipeline that collects features such as angle velocity, acceleration, etc. to train a deep neural network and deployed it. We are processing 30 million rows of data per hour for this detection on Databricks Platform.