Behavioral analysis
Machine learning-based anomaly detection
Behavioral Analysis uses ensemble machine learning models to build dynamic baselines for every device, user, and application on the network. The system learns normal communication patterns during the first 2 weeks and then detects statistical deviations indicating compromise, insider threat, or misconfiguration. The algorithms are automatically adjusted to the specifics of the environment, eliminating the need for manual tuning and reducing false positives.
Enterprise-grade protection compliant with regulatory requirements and security standards
Fast deployment with minimal resource overhead
Dedicated support from a certified partner
Easy integration with your existing infrastructure
Key features
- Ensemble ML with more than 50 algorithms building baselines for every device and user
- Adaptive detection thresholds adjusting to day, night, and weekend patterns
- Anomaly correlation over time creating attack chains and kill chain mapping
- Detection of slow-and-low attacks through multi-week trend analysis
- Explainable AI showing alert causes with confidence scores
Business benefits
- Detection of zero-day threats without known signatures and indicators of compromise
- Reduction of false alarms by 90% thanks to contextual baselines
- Automatic adaptation to environmental changes without reconfiguration
- Faster alert triage thanks to explainable detections
- Detection of insider threats invisible to rule-based systems
Why ExtraHop?
A pioneer in Network Detection and Response (NDR), using AI and machine learning to analyze network traffic in real time. ExtraHop Reveal(x) detects advanced threats, lateral movement, and anomalies that bypass traditional security controls.
Need Behavioral analysis in your organization?
As a certified ExtraHop partner, we'll help you deploy and configure the solution.