ITrust Reveelium UEBA

ITrust Reveelium UEBA is a behavioral analysis technology that combines SIEM, UEBA, threat hunting, XDR, and SOAR capabilities to detect known and unknown cyber threats. The platform uses artificial intelligence algorithms including machine learning and deep learning methods to analyze logs and identify abnormal behaviors of users and entities within information systems. The solution operates on a big data base capable of processing large volumes of data and logs from IT and OT sensors. It employs three complementary engines: behavioral analysis through UEBA, business rules correlation, and threat intelligence. The platform uses unsupervised learning algorithms to identify behavior patterns and detect contextual anomalies, incorporating graph theory, LSTM temporal neural networks, and supervised and unsupervised classification algorithms. Reveelium integrates the MITRE ATT&CK matrix to map tactical and technical dimensions of cyber attacks. The platform provides visualization of threats across the network, identifies impacted assets and IP addresses, and presents decision trees showing how abnormal behaviors were identified. It can perform both real-time analysis and offline forensic operations for post-incident investigation. The solution is agentless and non-intrusive, requiring only a central collector without probes. It can be deployed in the ITrust SOC or as a standalone system with log ingestion. The platform generates automated reports with threat indicators, criticality levels, histograms, and risk evolution over time.