Distributed Face Authentication With Real-Time Backend Processing
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Solution Overview
Problem
Existing user authentication methods, such as PIN and fingerprint recognition, lack a high security level that is easily achievable and efficient.
Innovation Solution
A distributed face recognition system where a face recognition application frontend is executed on a terminal device and a backend server, utilizing a backend server for complex calculations and extracting advanced face characteristics from video streams captured by the terminal device's camera, leveraging artificial intelligence and a communication network for secure authentication.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional authentication methods (PIN, fingerprint) are used, then ease of operation is maintained, but authentication security level is insufficient
Solution Approach 1:
The authentication system is segmented into two parts: a simple user-facing component (camera capture and basic interface) and a complex backend component (AI-based face characteristic extraction and comparison). This segmentation allows the user to interact with a simple system while the backend handles the complex security verification, resolving the contradiction between ease of operation and authentication security.
Solution Approach 2:
The patent replaces traditional mechanical authentication methods (physical fingerprint sensors, manual PIN entry) with an AI-based optical recognition system. The mechanical fingerprint sensor is substituted with a camera and AI algorithm that extracts advanced face characteristics, providing higher security while maintaining ease of use through automatic recognition.
2Reliability
If advanced face recognition with AI is implemented, then authentication security level is improved, but device complexity increases
Solution Approach 1:
The complex AI-based face recognition engine is extracted from the terminal device and placed on a remote server. The terminal device only needs to capture video streams and transmit them to the backend, while the complex computational tasks of extracting advanced face characteristics and performing authentication are handled by the remote server, reducing device complexity while maintaining high security.
Solution Approach 2:
A communication network acts as an intermediary between the terminal device and the backend server. This intermediary enables the terminal device to offload complex authentication computations to the remote server, allowing the system to achieve high security without increasing the complexity of individual devices.
3Productivity
If real-time video stream processing is performed, then authentication speed is improved, but energy consumption increases
Solution Approach 1:
The energy-intensive video stream processing and face characteristic extraction are extracted from the terminal device and performed on a remote server. The terminal device only performs low-energy tasks of capturing video streams and transmitting them, while the backend server handles the computationally intensive real-time processing, achieving fast authentication without excessive energy consumption at the device level.
Data Source
AI summary
A method for authenticating a user includes: an application frontend of a face recognition application, upon receipt of a face recognition request from an application backend of the face recognition application, causes a terminal device to activate a camera of the terminal device; the application frontend receives a video stream of a face of the user captured by the camera of the terminal device; the application frontend transmits the received video stream to the application backend; the application backend, upon receipt of the video stream, extracts a face characteristic of the user from the received video stream in real-time; and the application backend compares the extracted face characteristic with a stored reference face characteristic of the user and authenticates the user based on the extracted face characteristic matching the stored reference face characteristic.