Private Identity System Using Encrypted Biometric Feature Vectors
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Solution Overview
Problem
Current identification and authentication methods in computing environments are insecure, with user identifiers and passwords being inadequate, and existing augmentations like multifactor authentication failing to fully address security concerns.
Innovation Solution
A private identity system using fully encrypted biometric and behavioral information to securely identify users, enabling seamless identification across devices and switching between users with minimal overhead, employing pre-trained embedding networks and classification networks to generate and recognize encrypted feature vectors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional user identifiers and passwords are used for authentication, then the system is easy to operate, but the security is insufficient
Solution Approach 1:
The patent replaces traditional mechanical authentication systems (user identifiers and passwords) with a biometric-based authentication system using neural networks. The embedding network processes biometric data to generate encrypted feature vectors, which are then authenticated by classification networks, substituting the manual password entry mechanism with automated biometric recognition.
Solution Approach 2:
The patent introduces encrypted feature vectors as an intermediary between the biometric input and the authentication decision. These feature vectors serve as a secure representation that preserves privacy while enabling authentication, acting as a mediator that transforms raw biometric data into a form suitable for secure comparison and verification.
2Reliability
If multifactor authentication is implemented to augment security, then the security is improved, but the device complexity increases
Solution Approach 1:
The patent merges multiple authentication factors into a unified neural network-based system. Instead of implementing separate multifactor authentication mechanisms that would increase device complexity, the system combines biometric processing, feature extraction, and authentication verification into an integrated architecture using embedding and classification networks.
Solution Approach 2:
The patent changes the fundamental parameters of authentication from discrete factors (password, token, biometric) to a continuous feature space represented by encrypted feature vectors. This transformation allows the system to achieve high security through the complexity of the neural network processing rather than through multiple separate authentication factors.
3Reliability
If biometric data is processed for identification, then the security is enhanced, but the loss of information increases due to encryption
Solution Approach 1:
The patent creates encrypted copies of biometric data in the form of feature vectors that preserve the essential identification information while protecting the original biometric data. These encrypted feature vector copies enable authentication and identification functions without exposing the actual biometric information, maintaining security while preserving necessary information for system operation.
Data Source
AI summary
In various embodiments, a fully encrypted private identity based on biometric and/or behavior information can be used to securely identify any user efficiently. According to various aspects, once identification is secure and computationally efficient, the secure identity/identifier can be used across any number of devices to identify a user an enable functionality on any device based on the underlying identity, and even switch between identified users seamlessly all with little overhead. In some embodiments, devices can be configured to operate with function sets that transition seamlessly between the identified users, even, for example, as they pass a single mobile device back and forth. According to some embodiments, identification can extend beyond the current user of any device, into identification of actors responsible for activity/content on the device.