Real-time network threat detection using YOLO object detection on edge AI hardware. Sub-millisecond inference. Zero cloud dependency.
Patent Pending 7 Threat Classes Edge AI <0.5ms InferenceRaw packets are captured via raw sockets and mapped to flows using consistent hashing.
Network flows are converted to 2D Network Activity Images (NAIs) — 32×32 grids with 10 channels encoding packet size, protocol, timing, and flow behavior.
YOLO object detection runs on the NAI, identifying and localizing threats with bounding-box regression — not just classification.
Threats are classified, localized to specific flows, and reported in real-time. The oracle auto-labels data for continuous retraining.
Running on Raspberry Pi 5 + Coral Edge TPU
32×32 Network Activity Image — each pixel represents flow activity over a 30-second window
Anthropic's Claude Mythos Preview can autonomously find and exploit zero-day vulnerabilities in every major OS. Signature-based IDS can't detect novel AI-generated exploits. NetworkVision detects the behavioral pattern on the wire — port scans, C2 beacons, exfiltration — regardless of the specific exploit. The traffic shape is detectable even when the attack is brand new.
NetworkVision is patent-pending and seeking partners for edge security deployment.
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