How can machine learning (ML) be used to improve DDoS attack detection and response?

ML algorithms can analyze network traffic patterns to identify subtle anomalies that traditional methods might miss. They can learn normal traffic behavior and adapt to changing conditions, improving detection accuracy and reducing false positives. ML can also automate mitigation responses, such as dynamically adjusting firewall rules or rerouting traffic. However, ML models require continuous training and monitoring to remain effective against evolving attack techniques.