Synthetic Image Authentication Without Storing User Images
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Solution Overview
Problem
Conventional authentication methods requiring users to remember passwords and PIN codes are vulnerable to unauthorized access, and the use of user-specific images for authentication raises privacy and storage concerns due to the need to store sensitive data.
Innovation Solution
Utilizing generative models to create synthetic images based on user-specific data, allowing users to authenticate without storing the original images, thus maintaining privacy and reducing storage needs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If user-specific images are stored for authentication, then authentication security is improved, but privacy concerns and storage requirements increase
Solution Approach 1:
The patent creates synthetic images that copy the essential visual characteristics of user-specific images without storing the original images. The generative model learns the appearance patterns from a set of user images and produces synthetic versions that retain identifying features while eliminating the need to store sensitive original data, thus resolving the contradiction between security and storage requirements
Solution Approach 2:
The patent transforms the authentication approach by changing the parameters of image representation. Instead of storing and comparing original images directly, the system uses a generative model that captures image characteristics in a compressed parameter space, allowing authentication through synthetic image generation while reducing storage requirements and protecting privacy
2Measurement precision
If high-resolution images are stored for authentication, then image quality and recognition accuracy are improved, but data storage requirements increase exponentially
Solution Approach 1:
The system creates synthetic copies of high-resolution user images through a generative model. The model learns detailed image characteristics from high-resolution training images and generates synthetic versions that maintain recognition accuracy. This allows the system to achieve high measurement precision without storing the original high-resolution images, as the generative model captures the essential features in a compressed form
Solution Approach 2:
The patent applies parameter changes by transforming image data from pixel-space to a compressed latent space through the generative model. This parameter transformation enables the system to work with high-resolution image characteristics while storing only the compressed model parameters, exponentially reducing storage requirements while maintaining recognition accuracy
3Ease of operation
If conventional authentication methods (passwords and PIN codes) are used, then ease of operation is improved, but security against unauthorized access deteriorates
Solution Approach 1:
The patent replaces the mechanical authentication system (passwords and PIN codes that users must remember and type) with an image-based recognition system. Users authenticate by selecting images that match their preferences or characteristics, eliminating the need to remember complex passwords while providing more secure authentication that is harder for unauthorized users to guess or brute-force
Data Source
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AI summary
Methods and systems are described herein for improvements to authenticate users, particularly authenticating a user based on data known to the user. For example, methods and systems allow for users to be securely authenticated based on data known to the users over remote communication networks without storing the data known to the users. Specifically, methods and systems authenticate users by requiring users to select images that are known to the users. For example, the methods and systems may generate synthetic images based on the user's own images and require the user to select the synthetic image, from a set of a set of images, that is known to the user to authenticate the user. Moreover, the methods and systems alleviate storage and privacy concerns by not storing the data known to the users.