Systems and methods for functionally separating heterogeneous data for analytics, artificial intelligence, and machine learning in global data ecosystems
US12093426B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Oct 14, 2021 |
| Grant date | Sep 17, 2024 |
| Priority date | — |
| Expiry date | May 18, 2043 |
Classification
- Technology area (CPC H)Electricity
- CPC primaryH04L2209/56
- WIPO fieldDigital communication
- WIPO sectorElectrical engineering
Abstract
Systems, program storage devices, and methods for improving data privacy/trust/anonymity/pseudonymity and data value, wherein data related to a Data Subject can be used and stored, while minimizing re-identification risk by unauthorized parties and enabling data related to the Data Subject to be disclosed to an authorized party by granting access only to the data relevant to that authorized party's purpose, time, place, and/or other criterion via the obfuscation of specific data values. The techniques described herein maintain this level of privacy/trust/anonymity/pseudonymity, while empowering Data Subjects, e.g., consumers or customers of such authorized parties, by enabling protection of data at the desired level of engagement with various business entities. The techniques described herein also allow Data Controllers to perform General Data Protection Regulation (GDPR) and Schrems II-compliant (and surveillance-proof) data processing, via the functional separation of heterogeneous data (e.g., via the use of “Variant Twins”) from embedded trust and privacy controls.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.