How can machine learning be used to detect DDoS attacks targeting consumer IoT devices?

Machine learning models can be trained on network traffic data from IoT devices to identify patterns indicative of DDoS attacks. This includes analyzing packet sizes, source IP addresses, request frequencies, and other features. By learning the typical behavior of devices, the model can detect anomalies and classify them as malicious DDoS traffic.