Machine Learning & User and Entity Behavior Analytics (UEBA)

Identify, detect and mitigate insider and external cyber threats in real time.

Machine Learning

ISMAC machine learning algorithms help security teams save time by automatically identifying security incidents and threats, analyzing them, and even automatically responding to them in some cases. Machine learning is built into many modern security tools. It is gradually replacing older methods of inference, such as manually-defined rules and statistical correlations.

User & Entity Behavior Analytics

An average company can produce thousands of events per second to be analyzed.

Machine Learning and UEBA help automatize two basic questions:”

1- What happened?

2- What could happen?

UEBA stands for User and Entity Behavior Analytics, which means that it looks for patterns in the behavior of the users and machines that are interacting with the network.

Without Machine Learning, this job would be manual and with a high degree of mistakes.

By applying Machine Learning techniques directly into our ISMAC solution, it allows for the creation of analytical models, and also learns from historical data, while identifying deviations of normal behavior from the user.

It helps you understand how your normal user behaves inside your network, making it easier for you to identify potential threats or hacked users, machines or endpoints.

Identify Malicious Insider Threats

Uncover Compromised Accounts

Track Unauthorized Data Access & Exfiltration

Harness the Power of Full-Spectrum Analytics to Increase Visibility into User Behavior

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