Centrify Privilege Threat Analytics Service vs Splunk User Behavior Analytics comparison

Cyber adversaries are getting more and more sophisticated and therefore it is best practice to apply multiple security layers when protecting against privileged access abuse. Today’s threatscape requires security controls to be adaptive to the risk-context and to use machine learning to carefully analyze a privileged user’s behavior. Leveraging Centrify Privilege Threat Analytics Service can make the difference between falling victim to a breach or stopping it in its tracks.

Splunk User Behavior Analytics is a behavior-based threat detection is based on machine learning methodologies that require no signatures or human analysis, enabling multi-entity behavior profiling and peer group analytics for users, devices, service accounts and applications. It detects insider threats and external attacks using out-of-the-box purpose-built that helps organizations find known, unknown and hidden threats, but extensible unsupervised machine learning (ML) algorithms, provides context around the threat via ML driven anomaly correlation and visual mapping of stitched anomalies over various phases of the attack lifecycle (Kill-Chain View). It uses a data science driven approach that produces actionable results with risk ratings and supporting evidence that increases SOC efficiency and supports bi-directional integration with Splunk Enterprise for data ingestion and correlation and with Splunk Enterprise Security for incident scoping, workflow management and automated response. The result is automated, accurate threat and anomaly detection.