Why Most ML Firewalls Fail (And How We Fixed It with a Honeypot Feedback Loop)
This story is from 2026-08-23. It is preserved in the archive; the latest stories are on the live feed.
Deploying Machine Learning directly inline to block malicious network traffic sounds great on paper until you run into the Base Rate Fallacy [cite: 1]. In high-throughput enterprise networks processing millions of flows per minute, even a seemingly impressive 99% accuracy rate (1% False Positive Ra…
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- 2026-08-23 16:13 · DEV Community — Machine Learning
Why Most ML Firewalls Fail (And How We Fixed It with a Honeypot Feedback Loop)