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Edge inference · Active
Jetson Edge AI Security
A defensive telemetry runtime for edge devices, pairing live network capture with measured on-device inference and operator-reviewed alerts.
HardwareView on GitHub
The problem
Robots and edge devices sit on networks too. Sending all of their traffic to the cloud for analysis is slow and expensive, so the detection has to run on the device, within its power and compute budget.
Approach
- edge-traffic-sensor, a companion capture pipeline, uses Suricata over AF_PACKET and writes a fixed CSV schema that the inference side consumes.
- Development runs on an x86 RTX 5090 host. The production target is Jetson AGX Thor (ARM64).
- Models run through ONNX, and inference cost is measured on the device.
- Alerts go to an operator for review rather than triggering automatic action.
Design principles
One concern per change. A defensive boundary. The data contract matters more than convenience.
Status
Active.