Machine learning for automatic identification of points of interest for side channel leakage
US12177349B1 · kind B1 · utility
Assignee
Inventors
Key dates
| Filing date | Oct 11, 2021 |
| Grant date | Dec 24, 2024 |
| Priority date | — |
| Expiry date | Jun 29, 2042 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N3/084
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Methods, machine readable media and systems for evaluating, through one or more simulations, the leakage of sensitive data in an integrated circuit, such as cryptographic data or keys, are described. The embodiments can use machine learning models, such as one or more neural networks to generate one or more leakage related scores for each portion in a set of portions of the cryptographic data. In one embodiment, leakage data associated the first set of POIs with one or more neural networks is processed by the one or more neural networks to identify the POIs that leak the most and determine one or more scores for each portion in the set of portions of the cryptographic data.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.