Voice Consent Verification for Coercion-Resistant Identity Checks
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Solution Overview
Problem
Conventional user verification techniques are susceptible to counterfeiting and fail to determine whether biometric inputs are coerced or provided by intellectually incapacitated individuals, lacking robustness in distinguishing genuine from fraudulent identities and ensuring voluntary consent.
Innovation Solution
A system utilizing voice authentication, geolocation, and consent verification components to ensure that consent is voluntarily given and not coerced, incorporating modules for voice analysis, nystagmus, pupil, and blink rate analysis to assess intellectual capacity, with encrypted recordation of consent processes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional biometric verification techniques (facial recognition, fingerprint recognition) are used, then verification can be performed, but the system cannot determine whether the biometric input is a copy (mask or 3D-printed mold) or whether the user is intellectually incapacitated
Solution Approach 1:
The verification process is segmented into multiple independent analysis components: voice authentication analysis, nystagmus detection, pupil analysis, and blink rate analysis. Each component performs a specific function to assess different aspects of the user's state, collectively providing comprehensive verification that distinguishes genuine users from copyists and detects incapacitation.
Solution Approach 2:
The voice authentication system serves multiple functions simultaneously: it verifies identity, detects whether the input is a copy/recording, and assesses the user's intellectual capacity through analysis of speech patterns, nystagmus, pupil response, and blink rate. This multi-functionality resolves the contradiction by making a single system capable of addressing multiple verification challenges.
2Reliability
If document-based verification (credit cards, driver's license) is used, then verification can be performed, but the documents are easy to counterfeit
Solution Approach 1:
The system replaces document-based mechanical verification with biometric verification using voice authentication. Instead of relying on physical documents that can be copied, the system uses acoustic biometrics and physiological responses (nystagmus, pupil dilation, blink rate) that are inherently difficult to replicate, thereby eliminating the counterfeiting problem while maintaining verification capability.
3Reliability
If conventional authentication techniques are used, then verification can be performed, but they fail to determine whether the user's physical characteristic provision is coerced or provided while intellectually incapacitated
Solution Approach 1:
The system provides feedback about the user's physiological state during the verification process. By analyzing nystagmus, pupil response, and blink rate in real-time, the system can detect signs of coercion or incapacitation and provide feedback to determine whether the verification should be accepted, thereby protecting against harmful factors while maintaining verification reliability.
Data Source
AI summary
During a voice authentication process, a code is transmitted to a first user electronic address. A determination is made as to whether the code was received from the first user and a second user within a threshold time period, and if so, the first and second users are enabled to record a consent verification script. Characteristics of the first user recording are compared with those of a first user reference voice recording to determine whether they are from the same person. Characteristics of the second user recording are compared with those of a second user reference voice recording to determine whether they are from the same person. In response to determining that the first recording and the first user reference voice recording are from the same person and that the second recording and the second user reference voice recording are from the same person a consent verification indication is generated.