AI-Powered User & Entity Behavior Analytics
Detect insider threats, account compromises, and anomalous behaviors with advanced machine learning algorithms and quantum-secure behavioral analytics.
Behavioral Analytics Capabilities
Comprehensive user and entity behavior analysis with AI-powered threat detection
Advanced Machine Learning
Proprietary ML algorithms including Isolation Forest and LSTM Autoencoder for accurate behavioral analysis.
Real-Time Monitoring
Continuous monitoring of user and entity behaviors across your entire digital infrastructure.
Risk Scoring Engine
Dynamic risk calculation with composite scoring based on multiple behavioral indicators and context.
Threat Detection
Identify insider threats, account takeovers, and anomalous behaviors before they become security incidents.
Threat Detection Capabilities
Comprehensive coverage of insider threats, account compromises, and anomalous behaviors
Behavioral Anomalies
Unusual user activity patterns and deviations from normal behavior
Access Violations
Unauthorized access attempts and privilege misuse
Data Exfiltration
Large data downloads, unusual file access patterns
Lateral Movement
Suspicious network traversal and system hopping
Time-based Anomalies
Activities outside normal business hours or locations
Application Misuse
Unusual application usage and functionality abuse
Real-World Use Cases
Threat detection scenarios where Sentinel UEBA is designed to provide critical security insights
Insider Threat Detection
Identify malicious or compromised insiders attempting to access or exfiltrate sensitive data.
Account Takeover Prevention
Detect when external attackers gain access to legitimate user accounts and behave anomalously.
Privilege Escalation Monitoring
Monitor for unauthorized attempts to gain elevated privileges or access restricted resources.
Technical Capabilities
Enterprise-grade behavioral analytics with comprehensive integration options
Behavioral Analytics
Threat Detection
Integration & Response
Advanced Machine Learning Algorithms
AI techniques for accurate behavioral analysis and threat detection
Isolation Forest
Unsupervised anomaly detection algorithm specifically designed to identify rare and unusual behaviors.
LSTM Autoencoder
Deep learning model for sequence-based anomaly detection in time-series behavioral data.
Composite Risk Scoring
Multi-factor risk assessment combining multiple behavioral indicators and contextual information.
Detect Threats Before They Become Incidents
Experience advanced behavioral analytics and AI-powered threat detection with a personalized demonstration of Sentinel UEBA.