Signal Correlation for Remote Identity Verification
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Solution Overview
Problem
Existing technologies face challenges in remotely or electronically verifying the trustworthiness of inputs, such as documentation, due to the inability to physically manipulate and compare documents, leading to increased risks of identity fraud and deception.
Innovation Solution
A computer-implemented method and system for correlating signals, which involves determining a user's position in a journey, capturing and obtaining signal data from sensors, and using correlation models to determine if the data correlates to untrustworthiness, thereby enabling actions such as rejecting requests or initiating further authentication.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If remote or electronic verification of documentation is implemented, then convenience and accessibility are improved, but the ability to physically manipulate and compare documents is lost, increasing fraud risk
Solution Approach 1:
The patent introduces multiple intermediary sensors (cameras, microphones, accelerometers, gyroscopes, barometers) that mediate between the physical document and the remote verification system. These sensors capture environmental context, device motion, and document characteristics to create a digital representation that preserves physical verification capabilities in a remote setting.
Solution Approach 2:
The patent replaces mechanical physical manipulation of documents with electronic sensor-based detection systems. Instead of physically handling and examining documents, the system uses camera images, audio recordings, and motion sensor data to verify document authenticity and detect fraud remotely.
2Measurement precision
If multiple sensors and signal data collection are implemented, then fraud detection accuracy is improved, but system complexity increases
Solution Approach 1:
The patent segments the verification system into distinct functional modules: image capture module, audio capture module, motion sensing module, environmental sensing module, and correlation analysis module. Each sensor type captures specific aspects of the verification process, and the correlation model processes each data type separately before integrating results.
Solution Approach 2:
The patent employs a universal correlation model that processes multiple types of sensor data (image, audio, motion, environmental) through a single unified framework. This multi-functional approach allows the same computational infrastructure to handle diverse sensor inputs, reducing overall system complexity despite the variety of sensors used.
Data Source
AI summary
The disclosure includes a system and method for correlation of signals including determining, using one or more processors, a first position in a user journey; determining, using the one or more processors, a first set of signal data identified for capture at the first position in the user journey, the first set of environmental signal data including a representation, at a first time, of one or more of an environment of a user device and the user device in relation to the environment; obtaining, using the one or more processors, the first set of signal data, the first set of signal data including first sensor data obtained from a first sensor at the user device; and determining, using the one or more processors, based at least in part on the first set of signal data including the first sensor data, a correlation to untrustworthiness.