A six-stage patented pipeline that turns raw SIP signaling into a real-time fraud verdict — and an immutable audit trail — before the call ever completes.
SipShield ingests SIP signaling, CDRs, and metadata from your softswitch, SBC, or trunk. Key elements — originating and terminating numbers, routing, duration, geolocation, language identifier, caller behavior — are captured in real time.
Raw call data is parsed into classifying features. This is the same method described in U.S. Patent No. 12,432,294 — the parsing step that turns telecom noise into ML-ready structured data.
Local and remote call databases are queried for historical data from facilities of the same type. Current-call features are combined with that history into an n-dimensional feature vector.
The feature vector is fed to a machine-learning module coupled with an Artificial Neural Network. The network outputs call-ranking parameters that quantify fraud risk on multiple dimensions.
A predictive model turns those parameters into a fraud verdict in milliseconds. Verdicts above the threshold trigger automatic actions: reject the call, tear down the route, alert the NOC.
Every verdict, along with the feature vector that produced it, is recorded on a permissioned blockchain ledger — providing the immutable audit trail that regulators, carriers, and traceback groups expect.
Every stage above corresponds to claims in U.S. Patent No. 12,432,294. Read the full patent breakdown to understand what's protected and how it applies to your network.
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