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.
There are additional costs associated with the integrator.
The licensing costs is around 10,000 dollars.
There are additional costs associated with the integrator.
The licensing costs is around 10,000 dollars.
Microsoft Purview Insider Risk Management utilizes more than 100 ready-to-use indicators and machine learning models to effectively detect critical security risks originating from insiders, including IP theft, data leakage, and security violations. The solution enables organizations to expedite risk mitigation through enriched investigation tools and Adaptive Protection, which automatically enforces protection controls. Built with privacy by design, users are pseudonymized by default, and role-based access controls and audit logs are in place to help ensure user-level privacy.
