Microsoft Purview Insider Risk Management vs Splunk User Behavior Analytics comparison

Microsoft Purview Insider Risk Management is used to identify and mitigate internal threats, monitor risky activities, and ensure compliance with regulatory standards, tracking confidential information, detecting unusual behavior, and managing data protection.

Microsoft Purview Insider Risk Management provides actionable insights and automates risk management processes to enhance security and safeguard sensitive data. Users benefit from its ability to detect insider threats early and appreciate its comprehensive auditing capabilities and customizable risk indicators. It seamlessly integrates with existing systems, allowing for easy policy configuration and leveraging advanced machine learning algorithms. Users find the real-time alerts to enhance security monitoring and proactive risk mitigation. Its detailed incident reporting and efficient data protection are frequently commended.

• Early Detection: Identifies insider threats at an early stage.
• Comprehensive Auditing: Offers extensive auditing capabilities for thorough investigation.
• Customizable Risk Indicators: Allows for tailoring risk indicators to specific needs.
• Seamless Integration: Integrates effortlessly with existing systems.
• Easy Policy Configuration: Simplifies the setup of security policies.
• Advanced Machine Learning: Utilizes sophisticated algorithms for better threat detection.
• Real-time Alerts: Provides instant notifications to enhance monitoring.
• Detailed Incident Reporting: Generates comprehensive reports on incidents.
• Efficient Data Protection: Ensures confidential information is secure.

• Enhanced Security: Improved threat detection and mitigation.
• Actionable Insights: Helps in making informed security decisions.
• Automated Processes: Reduces manual effort in risk management.
• Compliance Assurance: Ensures adherence to regulatory standards.

In industries such as finance, healthcare, and legal, Microsoft Purview Insider Risk Management is implemented to secure client data, ensure regulatory compliance, and proactively mitigate internal threats. Organizations leverage its real-time alerts, advanced machine learning capabilities, and detailed reporting to maintain stringent security standards in highly regulated environments.

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.