Survey on AI in Network Security

This is the conclusion made by this survey:

The rapid evolution of threats highlights the need for advanced defensive strategies in cybersecurity. Traditional static defenses are becoming insufficient, making ML a critical tool for modern security measures. While ML shows promise in research, practical application has been slow due to challenges like limited data and the high cost of false negatives. Bridging the gap between theory and practice requires improving data quality, reducing false negatives, and deploying adaptive ML technologies. This will enhance threat detection efficiency and ensure resilient, future-ready cybersecurity frameworks.