Local Neuro-Mechanical Fingerprint Authentication
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Solution Overview
Problem
Existing user authentication methods, relying on anatomical and behavioral biometrics, are not foolproof, prone to privacy issues, and require centralized databases, leading to increased costs and risks, especially in mobile and decentralized environments.
Innovation Solution
The use of neuro-mechanical fingerprints (NFPs) captured by 3-D sensors and processed through signal processing algorithms to generate unique identifiers for local user authentication, avoiding the need for centralized databases and minimizing power consumption.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If centralized databases are used to store user authentication data, then authentication reliability is improved, but security risks and costs increase
Solution Approach 1:
The patent extracts the authentication verification process from centralized remote servers and implements it locally on the user's own device. The neuro-mechanical fingerprint data is processed and compared locally without being transmitted to or stored on external servers, eliminating the security vulnerability of centralized databases while maintaining authentication reliability through local processing capabilities.
2Measurement precision
If additional hardware is added to capture biometrics, then authentication precision is improved, but device complexity and cost increase
Solution Approach 1:
The patent replaces complex specialized biometric capture hardware with standard motion sensors (accelerometers, gyroscopes) that are already present in mobile devices. Instead of using dedicated fingerprint scanners or facial recognition cameras, the system captures neuro-mechanical fingerprint data through motion sensors that detect subtle physiological movements, thereby achieving high authentication precision without adding hardware complexity.
3Reliability
If behavioral biometrics are used for authentication, then authentication reliability is improved, but power consumption increases
Solution Approach 1:
The patent implements authentication by analyzing periodic physiological movements (such as hand tremors or micro-motions) that occur naturally during device interaction. Instead of requiring continuous power-intensive monitoring of user behavior, the system captures these periodic motions during normal device usage and uses them for authentication, thereby maintaining reliability while minimizing additional power consumption.
Data Source
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AI summary
In accordance with one embodiment, a method for locally verifying the identification of a user with an electronic device is disclosed. The method incudes regenerating a neuro-mechanical fingerprint (NFP) in response to a micro-motion signal sensed at a body part. In response to a plurality of authorized user calibration parameters, a match percentage of the neuro-mechanical fingerprint is determined. The match percentage is determined without the use of a calibration NFP that was previously used to generate the user calibration parameters. Access to the electronic device and its software applications is then controlled by the match percentage. If the match percentage is greater than or equal to an access match level, access to the electronic device is granted. If the match percentage is less than the access match level, access is denied. Subsequent access requires further regeneration of the NFP and a determination of its match percentage in response.