The challenge
An autonomous vehicle depends on connected software, communications, and physical components. A useful security view needs to consider how threats move across those layers.
ML-based IDS/IPS for ROS2 autonomous UGVs
A security approach for autonomous ground vehicles that connects machine-learning detection with visibility across the operating system, robotics middleware, network, and physical layers.
Product overview
The approach
Bring multi-layer telemetry into an intrusion detection and prevention workflow, with anomaly analysis, risk correlation, and a response path for robotic environments.
Capabilities
- Operating-system, ROS2, network, and physical-layer coverage
- Machine-learning-based intrusion detection
- Threat correlation and response workflows
- Research and validation described in the product documentation
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