Executive Vice President,Global Head at LTI - Larsen & Toubro Infotech
Reseller
2022-07-29T18:27:17Z
Jul 29, 2022
Securonix UEBA is used for lateral movement detection, ransomware detection, multiple malware detections, user activity monitoring, and behavior analysis. We have completed a large number of additional use cases based on specific effects and commitment.
Lead Security Engineer at a tech services company with 1-10 employees
Reseller
2022-02-04T22:46:21Z
Feb 4, 2022
We are using the solution for behavioral analysis of the users and behavioral analysis of network traffic. For example, if we know that there is an IP address that keeps reaching out, we confirm it with the client, put that in behavioral analysis and say, "Okay. This is a regular behavior." It's not going to trigger us if they reach out to a certain threshold. If that IP reaches out to over that threshold, then we are going to tell the client, "Something seems to be wrong over here. This machine does not go to that IP address a lot, but this is going on a lot today." From a behavioral analysis perspective, the use cases are data exportation by contractors, by determination, account accessing, removal of media. The version we are using is SNYPR.
Securonix User and Entity Behavior Analytics (UEBA) leverages sophisticated machine learning and behavior analytics to analyze and correlate interactions between users, systems, applications, IP addresses, and data. Light, nimble, and quick to deploy, Securonix UEBA detects advanced insider threats, cyber threats, fraud, cloud data compromise, and non-compliance. Built-in automated response playbooks and customizable case management work flows allow your security team to respond to threats...
Securonix UEBA is used for lateral movement detection, ransomware detection, multiple malware detections, user activity monitoring, and behavior analysis. We have completed a large number of additional use cases based on specific effects and commitment.
We are using the solution for behavioral analysis of the users and behavioral analysis of network traffic. For example, if we know that there is an IP address that keeps reaching out, we confirm it with the client, put that in behavioral analysis and say, "Okay. This is a regular behavior." It's not going to trigger us if they reach out to a certain threshold. If that IP reaches out to over that threshold, then we are going to tell the client, "Something seems to be wrong over here. This machine does not go to that IP address a lot, but this is going on a lot today." From a behavioral analysis perspective, the use cases are data exportation by contractors, by determination, account accessing, removal of media. The version we are using is SNYPR.
We use it for insider threat detection. It's appliance-based in the data center.