Anomaly detection is primarily at home in the fields of artificial intelligence, big data and smart data, as well as cybercrime and cybersecurity. The term describes a method for recognising unusual patterns or deviations from large amounts of data – essentially anything that doesn't fit the „norm“. Such deviations are referred to as „anomalies“.
The goal of anomaly detection is to draw attention to errors, problems, or even threats at an early stage. This method is indispensable, especially in cybersecurity: it helps to discover attacks on computer systems by tracking down unusual activities in the network.
A simple example: Hundreds of payments are processed in an online shop every day. Suddenly, many expensive purchases are made from a single credit card in a short space of time. Anomaly Detection recognises this unusual behaviour and sounds the alarm - because it could be a sign of fraud.
In practice, anomaly detection thus makes companies more secure and processes more efficient by making hidden problems visible before greater damage occurs. Through the continuous use of modern technology, this method is becoming increasingly important in the digital age.
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