Acoustic Biometric Authentication Using Hand Gesture Signatures
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Solution Overview
Problem
Current smartphone user authentication methods, such as password authentication, are inconvenient due to the frequent need for login, and existing technologies have not effectively addressed the challenge of providing a seamless and efficient authentication process.
Innovation Solution
A method using a combination of acoustic signals and motion data from sensors to authenticate users, where acoustic signals are transmitted and received by smartphone speakers and microphones, and motion data from accelerometer and gyroscope sensors is used to compare signatures against trained models, determining authentication based on similarity scores within a predetermined tolerance level.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If password authentication is used, then user authentication can be performed, but user convenience deteriorates due to frequent login requirements
Solution Approach 1:
The patent replaces the mechanical/password-based authentication system with an acoustic field-based system. Instead of requiring users to type passwords, the system uses acoustic signals to capture hand gestures and signature movements, transforming the authentication mechanism from textual input to acoustic signal processing. This substitution eliminates the need for frequent password entry while maintaining security through acoustic biometrics.
Solution Approach 2:
The patent introduces acoustic signals as an intermediary between the user and the authentication system. The acoustic field serves as a mediator that captures hand gesture information without requiring direct contact or manual input. The system uses acoustic signals to transmit signature data to the authentication model, enabling contactless and convenient verification while maintaining security.
2Ease of operation
If acoustic signals and motion data are used for authentication, then user convenience improves by eliminating password entry, but device complexity increases due to multiple sensors and processing requirements
Solution Approach 1:
The patent applies multi-functionality by utilizing existing smartphone sensors (microphones, accelerometers, gyroscopes) for multiple purposes. These sensors, originally designed for basic functions like audio recording and motion detection, are now employed for acoustic biometric authentication. The system leverages the universal capability of these sensors to capture both acoustic signals and motion data, reducing the need for dedicated hardware while achieving sophisticated authentication.
Solution Approach 2:
The patent merges acoustic signal processing with motion data analysis into a unified authentication system. By combining microphones, accelerometers, and gyroscopes into a single authentication pipeline, the system integrates multiple data sources to create a comprehensive biometric verification method. This merging approach consolidates what could be separate systems into one cohesive authentication mechanism, managing complexity through integration rather than separation.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach allows for efficient and accurate user authentication by capturing finger displacement and rotation features, reducing the need for frequent password entry and improving user convenience while maintaining security through the use of Dynamic Time Warping and machine learning models.
Implementation Method 1
A speaker of the mobile device is configured to transmit the acoustic signal. A microphone of the mobile device is configured to receive the reflected acoustic signal
Implementation Method 2
An accelerometer of the mobile device is configured to obtain motion data related to the user's hand movement and signature
Implementation Method 3
A gyroscope of the mobile device is configured to obtain motion data related to the user's hand movement and signature
Data Source
AI summary
A non-transitory computer-readable medium encoded with a computer-readable program which, when executed by a first processor, will cause a computer to execute a method of authenticating a user, the method including training a plurality of models. The method additionally includes sending, by a computer, an acoustic signal. Further, the method includes receiving, by the computer, a reflected acoustic signal, wherein the reflected acoustic signal comprises information about a signature. Moreover, the method includes receiving, by the computer, motion data about the information about the signature. The method additionally includes comparing the information about the signature to a model to generate a score. Additionally, the method includes deciding, based on the score, if the information about the signature is within a predetermined tolerance level.