From Partial Visibility to Multi-Layered Machine Learning (SigaML²) Insights
SigaML² Process-Oriented OT Cybersecurity is based on Multi-Level Machine Learning Insights that include unfiltered visibility into the physical assets and machinery at Level Zero.
SigaML² is a suite of real-time Machine Learning and Artificial Intelligence based solution that complement and enhance OT IDS cybersecurity products.
It applies ML and AI to all Levels (0-4) and identifies evolving OT cyber attack manifestations based on anomalies and discrepancies within and between the data.
The Multi-Layered approach —combining Level 0 and Levels 1-4 attack expression data — provides immediate detection of OT attacks even when false data injection is used by the attacker and where control systems are manipulated without the operators’ knowledge.
Early threat detection: Detects cyber-attacks by applying Machine Learning to identify anomalies and discrepancies within and between the Multi-Level (0-4) data.
Critical decision support: Provides a real-time, CISO OT Decision Support System (OT_DSS) for managing a cyberattack event.
Cyber forensics: Collects high resolution (10Hz) information from all phases – before, during, and after an attack occurred – to support Forensics in all the attack stages.
Process attack simulation: Helps CISO train both cyber and operational teams to prepare for real OT Cyber-attacks using safe attack scenarios simulations.
