Systems and methods for detecting potentially malicious content in decentralized machine-learning model updates
US11361100B1 · kind B1 · utility
Assignee
Inventors
Key dates
| Filing date | Mar 28, 2019 |
| Grant date | Jun 14, 2022 |
| Priority date | — |
| Expiry date | Mar 5, 2041 |
Classification
- Technology area (CPC H)Electricity
- CPC primaryH04L63/1441
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
The disclosed computer-implemented method for detecting potentially malicious content in decentralized machine-learning model updates may include (i) receiving messages communicated within a group of client devices for performing an update of a shared machine-learning model, (ii) determining a bias of a target message in the messages communicated from a target client device in the group with respect to a remaining number of the messages in the messages communicated from the other client devices in the group, (iii) assigning a confidence score to each of the other client devices based on the bias determined for the target message, the confidence score representing a likelihood of potentially malicious content in the target message, and (iv) performing, based on the confidence score, a security action that prevents the potentially malicious content from compromising the update of the shared machine-learning model. Various other methods, systems, and computer-readable media are also disclosed.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.