Find out what your peers are saying about Exabeam, IBM, Cynet and others in User Entity Behavior Analytics (UEBA).
| Product | Mindshare (%) |
|---|---|
| Splunk User Behavior Analytics | 5.7% |
| Proofpoint Insider Threat Management | 6.3% |
| Rapid7 InsightIDR | 4.3% |
| Other | 83.7% |
| Company Size | Count |
|---|---|
| Small Business | 20 |
| Midsize Enterprise | 5 |
| Large Enterprise | 6 |
| Company Size | Count |
|---|---|
| Small Business | 7 |
| Midsize Enterprise | 6 |
| Large Enterprise | 12 |
Proofpoint Insider Threat Management offers effective security by detecting and mitigating insider threats through advanced analytics and user behavior monitoring, addressing cybersecurity needs effectively.
Proofpoint Insider Threat Management focuses on protecting organizations by providing visibility into insider activity. It identifies risky behaviors and anomalies, allowing for quick response. The technology uses robust analytics and tracking to safeguard data and intellectual property. It integrates with security infrastructures for a comprehensive approach, helping IT teams respond to potential threats in real-time.
What features define Proofpoint Insider Threat Management?Proofpoint Insider Threat Management is widely used in industries such as finance and healthcare due to its ability to secure sensitive data and ensure compliance with industry regulations. Its implementation helps these sectors safeguard confidential information while maintaining operational integrity.
Parsing hundreds of trivial alerts. Managing a mountain of data. Manually forwarding info from your endpoints. Forget that. InsightIDR instantly arms you with the insight you need to make better decisions across the incident detection and response lifecycle, faster.
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.
