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WHAT OUR CUSTOMERS SAY
SCADvance XP® is a comprehensive security platform consisting of both software and hardware components designed for real-time monitoring of industrial networks.
What makes SCADvance XP® unique is its use of specialized ML/AI-based predictive models that adapt to each individual OT network configuration. This enables the system to detect anomalies more accurately within the monitored network and enables the detection of threats without signatures including zero-day attacks.
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See SCADvance XP in action
Scadvance XP® monitors industrial networks not at their edges, like most IT systems, but collects information directly from OT/ICS devices, analyzing all transmitted packets.
The hardware interfaces including Industrial Ethernet, serial and CAN enable SCADvanceXP® to monitor all types of industrial automation networks, providing security teams with insight into all existing connections and devices in real-time and helping them detect any undesirable communication within the OT network.
The Scadvance XP® detects devices connected to a protected network based on observed traffic. This way, a map of the protected network is created in the form of a graph of connections between network devices at the data link layer (Layer 2 OSI) and network layer (Layer 3 OSI).
Director of the ICT Security, Large European railway company
Scadvance XP by analyzing the correlation of anomalies and results of the work modules AI detects the most dangerous and unobserved anywhere else attacks.
The system has mechanisms that allow the building of prediction models dedicated individually for each logical connection separately, which significantly improves the quality of prediction and anomaly detection.
SCADvance XP® enables users to create customized views and reports based on their preferences and permissions.
100% PASSIVE
NON-INVASIVE MONITORING
POST-INCIDENT ANALYSIS (FORENSICS)
INDICATION OF ATTACK VECTORS
FULL INVENTORY OF NETWORK RESOURCES
AUTOMATED NETWORK MAPPING
SEAMLESS SIEM, SOAR, UEBA, PAM, FW INTEGRATION
SUPPORT FOR ETHERNET,
RS & CAN INTERFACES
AI/ML BASED NETWORK ANOMALY DETECTION