Distributed learning anomaly detector

This invention describes a system for detecting unusual behavior in computer networks. It works by storing a pre-configured set of machine learning rules, specifically for typical network devices, that can be easily moved around. These rules are then updated and fine-tuned using actual data collected from a specific part of the network to create a customized anomaly detector.

Why it matters: Filed before widespread MLOps maturity and advanced distributed ML frameworks. The claims' focus on portable, locally-trained models for network anomaly detection is now more practical to implement and manage.

Status: Not in forceListed as no longer active. The specific reason is not in the record we hold.
How hard to build: SpecializedMachine learning software system, network integration

3 AI reinvention directions for this patent

See all three

AI gives you a few directions you could take this. Pick one, and we check whether your version is different enough to patent, then write the filing.

Reinvent this with AI

Where this one came from

Every morning we go through millions of abandoned patents and pick out 15 worth your time. This was one of today’s.

This one

+10