Model selection in cybersecurity refers to the process of choosing the most appropriate machine learning or artificial intelligence model for a specific security task. This involves evaluating different models or AI architectures based on their performance, accuracy, resource requirements, and suitability for the intended application, such as intrusion detection or malware classification. The goal is to select a model that best meets the security objectives while balancing efficiency and effectiveness. Proper model selection is crucial, as it directly impacts the reliability and robustness of cybersecurity systems, helping organizations defend against evolving threats.