Systems and methods for privacy-enabled biometric processing
US11943364B2 · kind B2 · utility
Assignee
Inventor
Key dates
| Filing date | Feb 28, 2022 |
| Grant date | Mar 26, 2024 |
| Priority date | — |
| Expiry date | Feb 28, 2042 |
Classification
- Technology area (CPC H)Electricity
- CPC primaryH04L2209/42
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
In one embodiment, a set of feature vectors can be derived from any biometric data, and then using a deep neural network (“DNN”) on those one-way homomorphic encryptions (i.e., each biometrics' feature vector) an authentication system can determine matches or execute searches on encrypted data. Each biometrics' feature vector can then be stored and/or used in conjunction with respective classifications, for use in subsequent comparisons without fear of compromising the original biometric data. In various embodiments, the original biometric data is discarded responsive to generating the encrypted values. In another embodiment, the homomorphic encryption enables computations and comparisons on cypher text without decryption of the encrypted feature vectors. Security of such privacy enable biometrics can be increased by implementing an assurance factor (e.g., liveness) to establish a submitted biometric has not been spoofed or faked.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.