Webinar: Defeating Bots with Machine Learning
Cheating software has become so advanced that it can get around existing detection methods. In this webinar we cover how ML-driven cheat detection is able to flag not only known, but also new unseen bots and cheats.
We look into the different techniques of our machine learning approach and how we model human behavior and then compute the difference of new observations to this reference model. We discuss how much training data is required and how models are learning as your player base changes. We round-off with a Q&A discussion.
You learn about:
- How human behavior can be described by multiple models
- Data I should collect now to catch bots and cheaters later?
- How much data do I need to get started with cheat detection?
- Options for leveraging your player community in improving your cheat detection model training.
- Christoffer Holmgård
- Chris Carvelli
For more on our services for bot detection check modl:assure.
If you are interested in bot detection for your game send us an email at firstname.lastname@example.org.