What is Anomaly Detection?
Anomaly detection is a technique to identify unusual behavioural patterns by being statistically or mechanically different from the rest of the observations. Anomaly detection is a data science application that combines techniques like classification, regression and clustering.
Where is Anomaly Detection widely used?
Anomaly detection is used in many application domains such as Intrusion detection, Fraud detection, Data Leakage Prevention, Smart buildings, Novelty detection
Why is Anomaly detection important?
Organizations need to meet the fast-moving changes in data under interconnected operations to get the full business picture. By detecting anomalies, the presence of intended or unintended induced attacks, defects and faults are identified.
Techniques involved in Anomaly Detection
There are many techniques for anomaly detection such as One-class support vector machines, Distance-based techniques, Replicator neural networks and Machine learning based anomaly detection.
Benefits of Anomaly Detection
- Immediate alerts requiring less labour and costs
- Effective and efficient threat detection which outweighs manual detection