Anomalies

Anomaly detection, also known as outlier detection, is a branch of data mining that deals with identification of events, items, observations, or patterns that do not comply to a set of expected events or patterns. Basically, a different (anomalous) behavior is a sign of an issue that could be arising in the given dataset. Splunk provides commands to detect anomalies in real time, and this can useful in detecting fraudulent transaction of bank credit cards, network and IT security frauds, hacking activity, and so on. Splunk has various commands that can be used to detect anomalies. There is also a Splunk app named Prelert Anomaly Detective App for Splunk on the app store. It can be used to mine the data for anomaly detection. The following commands can be either used to group similar events or to create a cluster of anomalous or outlier events.

The anomalies command

The anomalies Splunk command is used to detect the unexpectedness in the given data. This command assigns a score to...