Machine learning for anomaly detection In data mining, anomaly detection is referred to the identification of items or events that do not conform to an expected pattern or to other items present in a dataset. Typically, these anomalous items have the potential of getting translated into some kind of problems such as structural defects, errors or frauds. Using machine learning for anomaly detection helps in enhancing the speed of detection.
Intrusions are those activities that can damage information systems. Intrusion detection has been gaining broad attention. Anomaly detection can be a key for solving intrusions, as while detecting anomalies, perturbations…
