User Behavior Analytics

(OBJ .)

Advanced cybersecurity strategy that uses big data and machine learning to analyze user behaviors for detecting security threats
Focuses on understanding user behavior within systems and networks to identify patterns and anomalies

Technology similar to UBA but extends the monitoring of entities like routers, servers, and endpoints in addition to user accounts
Enhances security by analyzing both user and entity behavior to detect anomalies

UBA leverages data analytics to collect and analyze user behavior data to establish normal behavior baselines
- Knowing the baseline makes it easier to spot anomalies
Machine learning algorithms are used to identify deviations from normal behavior, which may indicate security threats
UBA systems process data from various sources
- Network traffic
- User devices
- Application logs
Alerts are generated when anomalies are detected, which are then investigated by the security team

Early Detection of Threats
- UBA tools can identify potential threats before significant damage occurs, allowing for quicker and more effective responses
Insider Threat Detection
- Effective at identifying insider threats by detecting suspicious activities that deviate from typical behavior
Improved Incident Response
- Provides detailed information about user behavior, helping security teams respond effectively to incidents, such as compromised credentials or unauthorized actions