Which statement about anomaly detection systems is true?

Anomaly detection systems focus on identifying patterns or instances that deviate significantly from normal behavior or established patterns within a dataset. This ability is crucial in various applications, such as fraud detection, network security, and fault detection in manufacturing processes. By spotting these deviations, anomaly detection systems can alert users to unusual activities that may indicate potential issues or threats.

The option about forecasting is not accurate since anomaly detection primarily concentrates on identifying irregularities rather than predicting future events or trends. The statement regarding preventing all system breaches is also misleading, as while anomaly detection can help recognize and respond to potential threats, it cannot guarantee complete prevention. Additionally, the requirement for large amounts of labeled data is not universally true for anomaly detection; many systems can function effectively with unsupervised learning approaches that do not depend on vast labeled datasets.