How can AI and machine learning be leveraged to detect anomalies in IoT networks?

AI and machine learning can be applied to detect unusual activity and anomalies in IoT network traffic by analyzing patterns and behaviors in the data. Through the use of algorithms that can learn from historical data, AI systems can identify deviations from normal network behavior, which may indicate potential security threats or abnormal activities. By continuously monitoring and analyzing network traffic in real-time, AI algorithms can establish baseline behaviors and flag any deviations that require further investigation. This proactive approach enables early detection and mitigation of security threats in IoT networks.