Which technology identifies anomalies and threats by scanning multiple intrusion detection sources?

User and Entity Behavior Analytics (UEBA) is designed to enhance security monitoring by identifying anomalies in user and entity behavior. It does this by analyzing patterns across multiple data sources, including logs from various systems, network traffic, and user activities. UEBA relies on machine learning algorithms to establish a baseline of normal behavior for users and entities, allowing it to detect deviations that may indicate potential security threats or intrusions.

This technology is particularly effective in identifying sophisticated attacks that may not be caught by traditional security tools, as it provides a broader context for understanding interactions across different systems. By correlating data from multiple intrusion detection sources, UEBA can offer insights into behaviors that might suggest malicious activity, such as unauthorized access or data exfiltration.

In contrast, the other technologies listed focus on specific aspects of security. For instance, a Host-based Intrusion Detection System (HIDS) monitors and analyzes the internals of a computing system, primarily looking at events on that individual host rather than correlating data from multiple sources. Endpoint Detection and Response (EDR) emphasizes the monitoring and response to threats on endpoints but typically concentrates on individual devices rather than providing a comprehensive analysis across the network. Unified Extensible Firmware Interface (UEFI) relates to system firmware and