Detect Insider Threats with User Behavior Analytics

IBM® QRadar® User Behavior Analytics (UBA) analyzes user activity to detect malicious insiders and determine if a user’s credentials have been compromised. Security analysts can easily see risky users, view their anomalous activities and drill down into the underlying log and flow data that contributed to a user’s risk score. As an integrated component of the QRadar Security Intelligence Platform, UBA leverages out of the box behavioral rules and machine learning (ML) models to add user context to network, log, vulnerability and threat data to more quickly and accurately detect attacks.

Gain visibility into insider threats

Guard against rogue insiders and cyber criminals using compromised credentials. Uncover anomalous behaviors, lateral movement, threats and data exfiltration─with a user focus.

Improve analyst productivity

Easily identify risky users by applying machine learning (ML) and behavioral analytics to QRadar security data, calculate users’ risk scores and only raise alerts on high risk incidents.

Accelerate time to value

Generate meaningful insights within 24 hours. QRadar clients can download and install the UBA app quickly and easily from the IBM Security App Exchange.

Extend QRadar security features

The UBA dashboard is an integrated part of the QRadar console and helps extend capabilities of the QRadar Security Intelligence Platform.

Key Features

  • Detects insider threats based on user behavioral anomalies
  • Generates detailed risk scores for individual users
  • Integrates seamlessly with QRadar Security Analytics
  • Available from the IBM Security App Exchange

Product images

Dashboard
Dashboard
Risky Activity Timeline
Risky Activity Timeline
User Details
User Details
Watson
Watson

See how it works

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