Scanning and detecting threats in machine learning models
US11954199B1 · kind B1 · utility
2Cited by
2References
20Claims
0Family size
Assignee
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Key dates
| Filing date | Nov 8, 2023 |
| Grant date | Apr 9, 2024 |
| Priority date | — |
| Expiry date | Nov 8, 2043 |
Classification
- Technology area (CPC H)Electricity
- CPC primaryH04L63/1433
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A machine learning model is scanned to detect actual or potential threats. The threats can be detected before execution of the machine learning model or during an isolated execution environment. The threat detection may include performing a machine learning file format check, vulnerability check, tamper check, and stenography check. The machine learning model may also be monitored in an isolated environment during an execution or runtime session. After performing a scan, the system can generate a signature based on actual, potential, or absence of detected threats.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.