Neurophysiological Biometric Authentication Without Physical Contact
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Solution Overview
Problem
Existing authentication technologies face challenges in providing high security, convenience, and adaptability, as they can be replicated, require physical interaction, or are inconvenient due to environmental and user condition changes, and lack individualized authentication methods.
Innovation Solution
A neurophysiological biometric authentication system using machine learning to generate unique neuro-biometric identifiers (NBIs) from neurophysiological data, adaptable to user conditions and environments, without requiring physical interaction or memorization, and integrating multiple biometric modalities for enhanced security and reliability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If traditional biometric authentication (fingerprint, facial recognition) is used, then user convenience is improved, but security is worsened because these biometrics can be replicated or compromised
Solution Approach 1:
The patent replaces physical biometric systems (fingerprint sensors, facial cameras) with a neurophysiological system that measures electrical activity of the brain and nervous system. This substitution uses electrochemical signals instead of mechanical/physical traits, making the authentication more secure as these internal neural patterns are extremely difficult to replicate externally.
Solution Approach 2:
The system changes the fundamental parameter being measured from external physical characteristics to internal neurophysiological parameters (electrical potentials, firing rates, synaptic transmission patterns). This parameter change enables authentication based on the user's cognitive and neural state rather than static physical traits, improving both security and adaptability.
2Reliability
If physical biometric interaction is required, then authentication security is improved, but user convenience is worsened due to physical interaction requirements
Solution Approach 1:
The patent eliminates the need for physical interaction by replacing contact-based biometric sensors with non-contact neurophysiological measurement. The system can detect neural activity through electromagnetic fields or other non-invasive means, allowing authentication without the user touching or positioning themselves in specific ways relative to the device.
3Ease of operation
If voice-based authentication is used, then user convenience is improved, but security is worsened due to susceptibility to spoofing attacks and background noise
Solution Approach 1:
The patent replaces acoustic-based voice recognition with electrophysiological measurement of neural activity. This substitution moves from detecting sound waves in the air to detecting electrical signals within the nervous system, making the authentication immune to background noise and spoofing attempts since external acoustic interference cannot replicate internal neural patterns.
4Reliability
If knowledge-based authentication (passwords, security questions) is used, then security is improved, but user convenience is worsened due to password management complexity
Solution Approach 1:
The patent implements self-service authentication where the user's own neurophysiological characteristics serve as the credential. The system automatically captures and verifies neural patterns without requiring the user to remember, create, or manage any authentication data, eliminating password management complexity while maintaining high security through unique biological identification.
5Reliability
If two-factor authentication is used, then security is improved, but user convenience is worsened due to additional time and steps required
Solution Approach 1:
The patent merges multiple authentication factors into a single neurophysiological measurement process. By capturing the user's neural patterns, cognitive state, and physiological responses simultaneously through one integrated system, it replaces the sequential multi-step process of traditional two-factor authentication with a unified single-step verification, reducing time loss while maintaining or enhancing security.
6Ease of manufacture
If existing authentication technologies are used, then implementation is simplified, but adaptability to user condition changes is worsened
Solution Approach 1:
The patent implements a dynamic authentication system that continuously adapts to changes in the user's neurophysiological state. The system can detect and adjust to variations caused by stress, fatigue, illness, or environmental factors by comparing real-time neural patterns against updated baselines, maintaining authentication accuracy despite user condition changes unlike static traditional systems.
Data Source
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AI summary
The present invention relates to a neurophysiological biometric authentication system and associated method for securely authenticating a user to access a protected space managed by at least one device, said system comprising at least one processor comprising: a data centralization sub-processor configured to transmit centralization Metadata, wherein said data centralization sub-processor is configured to receive at least one first biometric data comprising at least one neurophysiological data through an associated data channel and transmit said at least one first biometric data to a user recognition sub-processor; said user recognition sub-processor configured to receive said at least one first biometric data and to output a recognition Metadata as comprising at least protocol Metadata and/or an authentication result to be transmitted to said at least one device to securely authenticate the user to access said protected space.