An anomaly is in general something irregular that deviates from the common rule. For example, when it comes to data analysis, an anomaly is a data unit which notably differs from the majority. With the abrupt rise of Technology, businesses have adopted AI-powered Anomaly Detection as a solution to quickly become aware of occurring anomalies and control them.


What is Machine Learning Anomaly Detection and what are its benefits?

Machine Learning Anomaly Detection is the use of algorithms in order to automatically detect anomalies in an IT system. When it comes to log management and security analytics platforms, Anomaly Detection plays a crucial part. It helps in the achievement of a higher level of security by conducting continuous monitoring in order to detect suspicious events and point out where an error is occurring.

Some of these events may be intrusion or attack attempts, where attackers try to invade and damage an IT system. Another example is network failures, whose consequences can affect any business’s performance. With the use of Anomaly Detection, organizations can not only deal with the problem effectively, but also identify the cause of such events and be prepared for similar incidents in the future.

In addition, Anomaly Detection can handle large amounts of data and provide adaptive and on-time alerting mechanisms. So, no matter how big the databases are and how many logs need to be managed, users apply reliable and uninterrupted monitoring to make sure data remain secure while operating in an ever-changing environment.


How does Anomaly Detection work in our Platform?

The first thing users should do when using is to ship logs.  Users may choose their preferred log shipper at the Log Shippers tab and follow the detailed guide on how to send their logs to the platform via Filebeat.

Through the Apps tab, users can select the dashboards that suit their needs. Access them at the Kibana Dashboards tab to get a visual interpretation of the log data.

The Anomaly Detection tool is at the Insights tab. Initially, users need to create a detector following these simple steps:

  1. Click on Detectors and then Create Detector.
  2. Choose a name and description for the Detector.
  3. Choose the preferred settings regarding the Data Source.

Furthermore, add a Data Filter. Users have the ability to add and apply as many filters as they want.

The next step is to define the way that the Detector should operate.

Define the model features in order to set the index fields which the Detector will search and find anomalies in. The maximum number of features that users can apply is five.

Now it’s all set! Users can create multiple Detectors if they want.

When this configuration is complete, the created Detectors will start monitoring inputs of information and provide insights by identifying and isolating anomalies. This information is visible and available at the Dashboard section of the Insights tab.

The ability to detect anomalies in almost real-time is achieved with the use of an advanced algorithm called Random Cut Forest (RCF). Taking Anomaly Grade and Confidence Score Value into consideration, this algorithm can single out an abnormal from a normal behavior.

After an anomaly has been detected, the Alerting feature of comes into the appliance, providing alert notifications about the problem to solve it before it becomes a real issue.



The development of Artificial Intelligence has helped businesses in various ways, one of which is the automatic recognition and prevention of hostile actions from damaging a system. Machine Learning Anomaly Detection is a must-have for an effective Cyber Security system, as it adds value by performing human actions at such a faster rate.

Our cloud-hosted solution with advanced features brings the functionality of centralized monitoring to your hands. Convert your data into actionable insights and maximize the performance of your infrastructure, or be notified of potential problems and take the appropriate actions. Sign-up for a free demo in order to realize the power of Logstail!

Logstail will re-adjust the way you monitor your data and will help you get more meaningful insights of your technical logs, via dashboards and powerful graphs, to stay alert for all possible dangers.

In Logstail we are also offering the full range of services required to effectively mitigate cyber-attacks. Incident response and consulting, penetration testing and red team operations are altogether aiming to help our customers mitigate their cyber incidents.

Contact us at  to get a tailored offer for your business or get a free consultation by our team of globally recognized security experts!

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