Selective Caller ID Verification for Impersonation Spoofing
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Solution Overview
Problem
Existing caller ID spoofing techniques, such as Do Not Originate (DNO) lists, are ineffective in distinguishing between legitimate and illegitimate calls, allowing spoofed calls to bypass blocking mechanisms, and require additional phone lines for legitimate callers to make outgoing calls.
Innovation Solution
Implementing a selective DNO system that uses criteria-based call blocking, including STIR/SHAKEN attestation, geographic restrictions, and AI/ML to identify and block spoofed calls while allowing legitimate calls, and creating a shared selective DNO repository across carriers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a Do Not Originate (DNO) list is implemented to block spoofed calls, then spoofed calls are reduced, but legitimate calls may be incorrectly blocked and additional phone lines are required for outgoing calls
Solution Approach 1:
The patent transforms the binary DNO blocking approach into a multi-parameter verification system using STIR/SHAKEN attestation levels (A, B, C), geographic location data, and AI/ML confidence scores. Calls are evaluated against multiple criteria simultaneously, allowing the system to distinguish legitimate from spoofed calls with higher precision and avoid blocking valid communications.
2Object-affected harmful factors
If traditional DNO blocking is applied to all calls from registered numbers, then spoofing is reduced, but call verification precision is insufficient to distinguish legitimate from illegitimate calls
Solution Approach 1:
The patent segments the call verification process into multiple independent validation layers: STIR/SHAKEN attestation verification, geographic location matching, AI/ML spoofing pattern detection, and real-time reputation scoring. Each layer independently evaluates specific aspects of call authenticity, and the combined results provide high-precision authentication that distinguishes legitimate from spoofed calls.
Solution Approach 2:
The patent introduces an intermediary AI/ML analysis layer that sits between the traditional DNO blocking mechanism and the actual call routing decision. This intermediary evaluates multiple data sources (attestation levels, geographic data, call patterns) and provides a confidence score that determines whether to block or permit the call, significantly improving detection precision.
3Reliability
If carriers implement individual DNO lists, then spoofed calls are blocked, but system complexity increases and shared verification infrastructure is lacking
Solution Approach 1:
The patent creates a universal shared verification infrastructure that all carriers can access through a common platform. The centralized system handles STIR/SHAKEN attestation validation, geographic location verification, and AI/ML spoofing detection for all participating carriers, eliminating the need for each carrier to independently implement and maintain complex verification systems while providing consistent spoofing protection across the entire network.
Data Source
AI summary
Aspects of the subject disclosure may include, for example, a device, including: a processing system including a processor; and a memory that stores executable instructions that, when executed by the processing system, facilitate performance of operations of: receiving a selection criteria for calls originating from a telephone number; detecting a call having a caller identification matching the telephone number; determining that the call does not meet the selection criteria; and blocking the call responsive to the determining. Other embodiments are disclosed.