Real-Time Image Capture for Identity Verification
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Solution Overview
Problem
Online networks face challenges in verifying the identity of users, leading to potential anonymity and fraudulent behavior, as self-reported information lacks independent verification.
Innovation Solution
A system requires users to participate in a real-time image-capture event, capturing video or still images of them performing tasks, which are then validated to ensure a human participant, and this evidence is made available to other users for trust assessment, with periodic re-captures and validation based on interactions or criteria.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If self-reported identifying information is collected during registration, then the registration process is simple and fast, but the accuracy and trustworthiness of the information cannot be fully trusted
Solution Approach 1:
The system performs preliminary actions by capturing video and collecting identity information during the registration process before the user actually uses the service. This advance capture and association of data ensures that verification is completed upfront, resolving the contradiction between simple registration and accurate identity verification.
Solution Approach 2:
The system introduces an intermediary validation mechanism that captures video evidence and associates it with user accounts. This intermediary layer between self-reported information and trust verification resolves the contradiction by providing objective evidence without complicating the user registration process.
2Measurement precision
If users are required to participate in real-time image-capture events with video recording, then identity verification accuracy is improved, but the complexity of the registration process increases
Solution Approach 1:
The system uses a multi-functional approach where a single video capture event serves multiple purposes: verifying identity, capturing biometric data, and creating trust evidence. This universal capture mechanism improves verification accuracy without requiring multiple separate verification systems, thus managing complexity.
Solution Approach 2:
The system merges the collection of identity information and video capture into a single integrated process. By combining these functions that occur simultaneously during one user event, the system achieves high verification accuracy while avoiding the complexity of separate verification steps.
3Reliability
If captured video evidence is made available to other users for review, then the ability to detect impostors is enhanced, but the loss of user privacy increases
Solution Approach 1:
The system applies local quality by making video evidence selectively available - only certain users or user groups can access the verification evidence of specific users. This selective availability enhances impostor detection where needed while preserving privacy in other contexts, resolving the contradiction between reliability and privacy loss.
Data Source
AI summary
A method of generating irrefutable evidence of registration that cannot be repudiated by the registrant for a network-based application is described. The method initiates an image capture session to capture a plurality of images of an individual user. The method, during the image capture session, provides a sequence of tasks to be performed by the individual user in order to validate the image capture session in capturing an image of a person participating in a real-time event.