Tag: User Behavior Analytics (UBA)

When users are granted inappropriate access to privileged accounts, they open the entire IT environment to vulnerabilities — and make it easier for malicious actors to infiltrate corporate networks.

According to a recent insider threat report, 60 percent of risk assessments identified users who tried to bypass their employer's security measures using private or anonymous browsing.

Organizations need a privileged account management (PAM) solution that integrates seamlessly with the existing security environment — and helps security teams enforce least privilege policies.

Security analysts can maximize the effectiveness of their incident response capabilities by integrating disparate tools such as database firewalls and UBA with a strong SIEM solution.

A UBA solution powered by machine learning enables security teams to model normal behavior and track subtle changes in user activity to identify malicious insiders.

To defend their confidential data from increasingly sophisticated cybercriminals, security teams must leverage machine learning to perform analytical tasks that are too tedious for humans to complete.

Security professionals need a comprehensive way to analyze user behavior, automatically respond to reports of suspicious activity and manage user access accordingly to thwart insider threats.

Security analysts need access to deep network insights in the form of user behavior analytics to unlock the full potential of technologies such as artificial intelligence and machine learning.

Unified identity and access management solutions from IBM enable security teams to silently protect their networks without disrupting the user experience.

IBM QRadar offers all the bells and whistles — and cowbell — security teams need to enhance their SIEM capabilities without paying an arm and a leg.