Ai identification of computer resources subjected to ransomware attack
US12248574B1 · kind B1 · utility
Assignee
Inventors
Key dates
| Filing date | Jul 18, 2024 |
| Grant date | Mar 11, 2025 |
| Priority date | — |
| Expiry date | Jul 18, 2044 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06F2221/034
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A method provides a set of computer data statistical profiles derived from a corresponding set of samples of computer data to a ransomware detection system and obtains a prediction of the likelihood of a ransomware attack in the set of samples of computer data. The system utilizes a machine learning system trained to achieve data models, with each model trained initially on a corresponding cluster of curated computer data statistics profiles, each cluster including statistics characterizing a corresponding cluster of curated samples resulting from exposing a selection of raw data samples to processing by actual ransomware. Each model is subject to iterations against initial validation data until performance convergences, with sample sources from the same backups not being present in both training and validation models. The models have been subject to final validation against actual customer data to address data drift that would otherwise result in excessive false predictions.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.