Dynamic monitoring and securing of factory processes, equipment and automated systems
US11669058B1 · kind B1 · utility
Assignee
Inventors
Key dates
| Filing date | Jul 15, 2022 |
| Grant date | Jun 6, 2023 |
| Priority date | — |
| Expiry date | Jul 15, 2042 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06F21/566
- WIPO fieldControl
- WIPO sectorInstruments
Abstract
A training set that includes at least two data types corresponding to operations and control of a manufacturing process is obtained. A deep learning processor is trained to predict expected characteristics of output control signals that correspond with one or more corresponding input operating instructions. A first input operating instruction is received from a first signal splitter. A first output control signal is received from a second signal splitter. The deep learning processor correlates the first input operating instruction and the first output control signal. Based on the correlating, the deep learning processor determines that the first output control signal is not within a range of expected values based on the first input operating instruction. Responsive to the determining, an indication of an anomalous activity is provided as a result of detection of the anomalous activity in the manufacturing process.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.