Anomaly detection is particularly at home in the fields of artificial intelligence, big data and smart data as well as cybercrime and cybersecurity. The term describes a method used to recognise unusual patterns or deviations from large amounts of data - in other words, anything that does not fit the "norm". Such deviations are referred to as "anomalies".
The aim of anomaly detection is to draw attention to errors, problems or even threats at an early stage. This method is particularly indispensable in cybersecurity: it helps to detect attacks on computer systems by detecting 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 makes companies more secure and processes more efficient by making hidden problems visible before major damage occurs. Due to the constant use of modern technology, this method is becoming increasingly important in the digital age.
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