Anonymous Driver Matching Using Irreversible Facial Feature Vectors
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Solution Overview
Problem
Existing shared vehicle management systems fail to protect driver privacy by storing facial images or IDs, violating privacy laws and requiring significant storage and management costs, while also risking exposure of passenger privacy.
Innovation Solution
A system that irreversibly encodes driver images into facial feature vectors, managing driving information anonymously by generating and matching these vectors without storing the original images, allowing accurate classification and management of driver data while ensuring privacy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If real names and contact information are collected for ride-sharing matching, then matching accuracy and service reliability are improved, but driver anonymity and personal information security deteriorate
Solution Approach 1:
The patent introduces a trusted third-party authority (government agency or certification body) as an intermediary to verify and certify driver identities. This mediator enables reliable identity verification and matching while maintaining driver anonymity through certified pseudonyms, resolving the contradiction between service reliability and anonymity protection
Solution Approach 2:
The system creates and uses certified copies of driver identity information rather than handling original personal data. Drivers receive certification codes that serve as verified copies of their identity, enabling accurate matching and reliability while preventing exposure of actual personal information, thus protecting anonymity
2Measurement precision
If detailed personal information is stored for service verification, then verification accuracy is improved, but information security risks and privacy exposure increase
Solution Approach 1:
The patent extracts only the essential verification elements from complete personal information. Instead of storing detailed personal data, the system stores and processes only certification codes and verified identity attributes, achieving accurate verification while minimizing privacy exposure by taking out only what is necessary
Solution Approach 2:
The system applies different quality levels of information protection to different data elements. Sensitive personal information is fully protected with high anonymity, while certification verification data is made available with appropriate precision. This local differentiation of information quality enables accurate verification where needed while maintaining strong privacy protection where possible
3Productivity
If personal information is shared among service providers, then service coordination and matching efficiency are improved, but information security vulnerabilities and unauthorized access risks increase
Solution Approach 1:
The patent introduces a centralized certification authority as an intermediary that manages all personal information securely. Service providers do not directly share or access each other's personal data; instead, they interact through the intermediary using certification codes, which improves coordination efficiency while eliminating security vulnerabilities from direct information sharing
Solution Approach 2:
The system enables service coordination through sharing of certified identity copies rather than original personal information. Matching and service delivery are accomplished using verification codes that represent drivers' identities without exposing actual personal data, thereby improving productivity while preventing security vulnerabilities
Data Source
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AI summary
A driver anonymity-ensured shared vehicle-driving information management system includes a main camera, a sensor, an auxiliary camera, a memory unit, and a processor. The processor includes a driving record generation section configured to generate a driving record of the vehicle on the basis of an image taken by the main camera and sensing data detected by the sensor, a facial feature vector extraction section configured to extract a driver facial feature vector by irreversibly encoding the driver image taken by the auxiliary camera so that the driver image is not able to be restored to the original driver image, and an anonymous driver driving information storage section configured to match the driver facial feature vector with the driving record and stores the matched data in the memory unit.