"What I like about IBM QRadar User Behavior Analytics is that it uses machine learning algorithms to generate risk scoring for the user activity. I also like that it syncs with our Active Directory users, so it really has full coverage for all users in our environment."
"The scalability is very good. It's not a problem."
"I have used IBM QRadar User Behavior Analytics in a Cloud Pak on Amazon, and there it runs on top of it and is easy to assess. Additionally, I have installed processes and characters."
"It has a powerful GUI where you can put together your use cases, and don't have to write your own scripts."
"QRadar shows very effective correlations. If you combine all the logins plus user behavior and the current intelligence, it gives a very good correlation for business. I think it reduces the false positives in user activity monitoring because there is a lot of social information to correlate with other data."
"I really like the feature we have with the logs, that if there are any credit card numbers being used, like a PII, you can just use rejects and you can mask it. This is a really good feature in QRadar."
"IBM QRadar User Behavior Analytics has easy architecture, has a good portfolio and integration."
"The feature that I find the most useful is that IBM QRadar User Behavior Analytics is free of charge. It's a fully free product that can be installed on top of IBM QRadar SIEM."
"One of the most valuable features is UEBA. It's pretty helpful for us to make sure of our thresholds for any of our clients."
"The solution could improve by having more out-of-the-box use cases."
"I'm not sure about the stability just yet. We've observed a few issues and we raised a supporting ticket for it."
"The user interface and configurability of IBM QRadar User Behavior Analytics can be improved. It has a lot of pre-configured settings and not many things can be changed. It also needs more integrations. Currently, User Behavior Analytics is integrated only with IBM QRadar. It could have deeper integrations. It can also have more complicated scoring models. Currently, it has a very simple linear scoring model for users."
"From a functionality point of view there are issues sometimes."
"What needs to be improved in IBM QRadar User Behavior Analytics is the user experience. It's not optimal. Some screens are a bit clunky. The solution needs to be more user-friendly."
"While the interface is easy to use, it could be a little more responsive."
"Whenever we are upgrading or installing any type of patch, at that time we have some delays."
"We sometimes get an error about the hard drive. Approximately once in two months, we can't find the logs, and they go missing, which is a terrible issue. We are getting support for this issue from our support company."
"The area that needs improvement is reporting."
The User Behavior Analytics for QRadar (UBA) app is a tool for detecting insider threats in your organization. It is built on top of the app framework to use existing data in your QRadar to generate new insights around users and risk. UBA adds two major functions to QRadar: risk profiling and unified user identities.
Risk profiling is done by assigning risk to different security use cases. Examples might include simple rules and checks such as bad websites, or more advanced stateful analytics that use machine learning. Risk is assigned to each one depending on the severity and reliability of the incident detected. UBA uses existing event and flow data in your QRadar system to generate these insights and profile risks of users.
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 quickly, accurately, and efficiently
IBM QRadar User Behavior Analytics is ranked 8th in User Behavior Analytics - UEBA with 10 reviews while Securonix UEBA is ranked 23rd in User Behavior Analytics - UEBA with 1 review. IBM QRadar User Behavior Analytics is rated 7.4, while Securonix UEBA is rated 0.0. The top reviewer of IBM QRadar User Behavior Analytics writes "Stable and solid security intelligence but lacks some functionalities ". On the other hand, the top reviewer of Securonix UEBA writes "Useful for behavioral analysis of users and behavioral analysis of network traffic". IBM QRadar User Behavior Analytics is most compared with Splunk User Behavior Analytics, Microsoft Defender for Identity, Cynet, Exabeam Fusion SIEM and LogRhythm Enterprise UEBA, whereas Securonix UEBA is most compared with ArcSight Analytics, Exabeam Fusion SIEM, ArcSight Interset / Intelligence and Rapid7 InsightIDR.
See our list of best User Behavior Analytics - UEBA vendors.
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