Model training is the process of teaching an artificial intelligence (AI) or machine learning (ML) system to recognize patterns and make decisions by exposing it to large datasets. In cybersecurity, this often involves feeding the model with examples of both normal and malicious behaviors, allowing it to learn how to detect threats, anomalies, or intrusions. The data used for training can include user interactions, network traffic, or system logs, unless such data is specifically excluded for privacy or compliance reasons. Effective model training is crucial for developing robust AI-driven security solutions that can adapt to evolving cyber threats.