Deep learning-based detection and data loss prevention of image-borne sensitive documents
US11537745B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Dec 9, 2020 |
| Grant date | Dec 27, 2022 |
| Priority date | — |
| Expiry date | Dec 9, 2040 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N20/00
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
The technology disclosed relates to distributing a trained master deep learning (DL) stack with stored parameters to a plurality of organizations, to detect organization sensitive data in images, referred to as image-borne organization sensitive documents, and protecting against loss of the image-borne organization sensitive documents. Disclosed is providing organizations with a DL stack update trainer, under the organizations' control, configured to allow the organizations to perform update training to generate updated DL stacks, without the organizations forwarding images of organization-sensitive training examples, and to save non-invertible features derived from the images, ground truth labels for the images, and parameters of the updated DL stacks. In particular, the technology disclosed relates to receiving, from a plurality of the DL stack update trainers, organization-specific examples including the non-invertible features of the organization-sensitive training examples and the ground truth labels, and using the received organization-specific examples to update the trained master DL stack.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.