Cybersecurity

Detecting & Responding to Intrusions

Defending Critical Infrastructure

Livermore researchers are building intelligent detection capabilities to automatically respond to unknown cyber threats.

To anticipate unknown or unfamiliar tactics that may be deployed by advanced adversaries, we are using deep-reinforcement learning to identify anomalous behavior that could disrupt a networked system.

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Program Highlights

Direwolf

This program supports the CyberSentry program within the Department of Homeland Security's Cybersecurity and Infrastructure Security Agency by monitoring nation-wide IT and OT networks of critical infrastructure entities using the Direwolf tool.  LLNL develops novel analytics to detect advanced threats to these networks and provides analysts who monitor and work with participating entities to identify and mitigate threats.

Eye on Operational Networks (EyeON)

Sponsored by the Department of Energy's Office of Cybersecurity, Energy Security and Emergency Response, EyeON is a firmware inventory and threat analysis tool that is used by utility organizations when moving software updates into Operational Technology environments.  Anonymized metadata are sent securely to LLNL for compilation, analysis and anomaly detection.  If anomalies are detected, partner utility organizations are alerted for further investigation and remediation.

Skyfall

Skyfall is a hardware-in-the-loop testbed that connects real-world equipment, including a grid-scale power substation with high performance computers.  In Skyfall, we are able to model impacts of malicious attacks or adverse weather events to transmission and distribution systems.

Join Our Team

The Global Security Directorate at LLNL offers a diverse, collaborative environment where multidisciplinary teams work together to support the Lab’s mission and address a range of global and national security needs. Find impactful careers, talented teams and a great company culture.

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