Identity Verification System for IoT Fraud Prevention
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Solution Overview
Problem
In electronic communication infrastructures, there is a challenge in securely tying a communications device to a real-world identity to prevent fraud and unauthorized access, especially in environments like the Internet of Things, where instances of fraud and deception are common, and existing fraud-detection and user authentication processes are not fully effective.
Innovation Solution
A method and apparatus that access a data store to verify signal packets from a communications device, determining if a subscriber account identifier or unique alias is bound to a real-world identity, by checking deterministic events such as device reputation, historical behavior, and biometric parameters, and establishing ties between the real-world identity and digital entities like email addresses or financial accounts.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If existing fraud-detection and user authentication processes are implemented, then security against fraud and unauthorized access is improved, but the complexity of the authentication system increases
Solution Approach 1:
The authentication system is segmented into multiple independent verification components: device reputation analysis, historical behavior verification, deterministic event detection, and biometric parameter validation. Each component operates independently to verify different aspects of identity, allowing the system to maintain high security while managing complexity through modular architecture
Solution Approach 2:
The patent introduces an intermediary verification layer that acts as a mediator between the user and the system. This intermediary analyzes device reputation, behavioral patterns, and deterministic events to create a trust score, which then determines the level of authentication required. This intermediary layer simplifies the overall system by providing a centralized decision-making mechanism that coordinates multiple verification methods
2Measurement precision
If multiple verification methods including device reputation, historical behavior, and biometric parameters are used, then the accuracy of identity verification is improved, but the time required for authentication increases
Solution Approach 1:
The system performs preliminary actions by continuously monitoring and storing device reputation data, historical behavior patterns, and deterministic events in advance of actual authentication needs. This pre-computed information is readily available when authentication is required, eliminating the need for real-time analysis of behavioral patterns and significantly reducing authentication time while maintaining high verification accuracy
Solution Approach 2:
The patent implements partial verification by adjusting the number and type of verification methods based on the calculated trust score. For high-trust scenarios, only essential verification steps are performed, reducing authentication time. For low-trust scenarios, all verification methods including biometric parameters are activated, ensuring high accuracy when needed most
3Reliability
If deterministic events and historical behavior analysis are implemented, then the ability to detect fraud is improved, but the data processing requirements increase
Solution Approach 1:
The system extracts only the most relevant and discriminative features from deterministic events and historical behavior data for analysis. Instead of processing complete historical records, the system identifies and extracts key behavioral indicators and deterministic event patterns that are most predictive of fraud, significantly reducing data processing requirements while maintaining high fraud detection capability
Solution Approach 2:
The patent transforms raw behavioral data and deterministic events into standardized parameters and metrics that are easier to process and compare. By converting diverse data sources into unified parameter formats with standardized schemas, the system reduces the computational complexity of data processing while preserving the essential information needed for accurate fraud detection
Data Source
AI summary
Briefly, example methods, apparatuses, and/or articles of manufacture are disclosed that may be utilized to bring about accessing a data store to determine that signal packets have been received, via an electronic communications network, from a communications device that is to be verified. The communications device being co-located with a real-world identity. The method may additionally include electronically determining that a subscriber account identifier or a subscriber-unique alias is bound to an account held by the real-world identity and electronically tying the subscriber account identifier or the subscriber-unique alias to the real-world identity in response to electronically verifying the communications device after determining that the signal packets have been received from the communications device and in response to electronically determining that the subscriber account identifier or the subscriber-unique alias is bound to the account held by the real-world identity.