An AI-supported anomaly-based intrusion detection system (IDS) is a security technology that uses advanced machine learning algorithms to analyze network traffic in real-time and identify patterns that deviate from normal behavior. The system continuously monitors the network for any unusual or abnormal activities, and when it detects such patterns, it raises an alert. The AI-supported anomaly-based IDS uses various techniques such as supervised learning, unsupervised learning, and semi-supervised learning to perform anomaly detection. Once an alert is raised, the system can take appropriate actions to protect the network, such as blocking the suspicious traffic, isolating the affected system, or triggering an incident response plan. The AI-supported anomaly-based IDS can also provide detailed information on the nature and source of the attack, which can be used to improve the security of the network. In summary, AI-supported anomaly-based IDS is an advanced security technology that uses machine learning algorithms to detect unknown attacks by identifying patterns that deviate from normal behavior. It continuously monitors the network and raises an alert when it detects any abnormal activities and can take appropriate actions to protect the network.