Multimodal Authentication Flow for Lower User Burden
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Solution Overview
Problem
Conventional multi-factor authentication systems increase user burden and data handling complexity, reducing user convenience and efficiency.
Innovation Solution
An authentication system that integrates face and voice recognition with password input, where a terminal device acquires user data to extract authentication information, including face images and voice patterns, and transmits them to a server for multi-factor authentication, optimizing data handling and reducing user operations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If multi-factor authentication using multiple types of authentication information is implemented, then authentication security is improved, but user burden and operation complexity increase
Solution Approach 1:
The patent combines multiple authentication factors (face image, voice, password) into a single integrated authentication process. The terminal device simultaneously captures face images and voice signals, and the server device processes all these factors together to make an authentication decision, thereby maintaining high security while simplifying user operations.
Solution Approach 2:
The system performs preliminary acquisition of authentication information (face image and voice) before the actual authentication decision is made. The terminal device continuously monitors and stores these biometric data in advance, so that when authentication is required, the process can proceed quickly without requiring the user to manually provide each piece of information separately.
2Measurement precision
If multiple types of authentication information are collected and transmitted, then authentication accuracy is improved, but data transmission volume and handling complexity increase
Solution Approach 1:
The server device extracts only the essential authentication information from the transmitted data. Instead of processing complete raw face images and voice recordings, the system extracts key features and characteristics from these data types, thereby maintaining authentication accuracy while significantly reducing the amount of data that needs to be transmitted and processed.
Solution Approach 2:
The authentication information is segmented into distinct types (face image data, voice signal data, password information) that are processed independently but collectively contribute to the authentication decision. This segmentation allows for optimized transmission and processing of each data type according to its specific requirements.
Data Source
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AI summary
In order to enhance convenience in an authentication system using a plurality of types of authentication, a terminal device 10 detects a face from an image of a user (S1) and then displays a password (S2), and detects an utterance voice when the password is uttered (S3) and then starts to store a moving image (S4). The terminal device 10 recognizes the content of utterance from the voice (S5), cuts out, from moving image data, a face image at a timing of each of syllables of the content of utterance (S6), and transmits the face image, the content of utterance, and the voice, as authentication data, to a server device 20. The server device 20 performs multi-factor authentication including face authentication, voiceprint authentication, face-voice matching authentication, password collation, and the like, by using the authentication data received from the terminal device 10.