Defending against model inversion attacks on neural networks
US10733292B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Jul 10, 2018 |
| Grant date | Aug 4, 2020 |
| Priority date | — |
| Expiry date | Jan 21, 2039 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06F2221/034
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Mechanisms are provided for protecting a neural network model against model inversion attacks. The mechanisms generate a decoy dataset comprising decoy data for each class recognized by a neural network model. The mechanisms further configure the neural network model to generate a modified output based on the decoy dataset that directs a gradient of the modified output to the decoy dataset. The neural network model receives and process input data to generate an actual output. The neural network model modifies one or more actual elements of the actual output to be one or more corresponding modified elements of the modified output, and returns the one or more corresponding modified elements, instead of the one or more actual elements, to the source computing device.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.