Anomaly detection is the process of identifying data points, events, or behaviors that differ significantly from an established pattern of normal activity. Instead of looking only for known problems, an anomaly detection system learns or defines what typical behavior looks like and flags unusual observations for investigation. Depending on the application, it can use statistical methods, machine learning, rules, or a combination of approaches.
In cybersecurity, it can identify unusual login activity or unexpected network behavior. In industrial operations, it may detect abnormal equipment readings before a failure occurs. The technique is also used for fraud detection, quality control, predictive maintenance, and system monitoring, where recognizing deviations early can support faster investigation and response.
