Forecasting and classifying cyber-attacks using crossover neural embeddings
US10015190B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Nov 16, 2017 |
| Grant date | Jul 3, 2018 |
| Priority date | — |
| Expiry date | Nov 16, 2037 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N3/08
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A first collection including a first feature vector and a Q&A feature vector is constructed. A second collection is constructed from the first collection by inserting noise in at least one of the vectors. A third collection is constructed by crossing over a feature vectors of the second collection with a corresponding feature vector of a fourth collection. The second and the fourth collections have a property similar to one another. Using a forecasting configuration, a vector of the third collection is aged to generate a changed feature vector, the changed feature vector containing feature values expected at a future time. The changed feature vector is input into a trained neural network to predict a probability of the cyber-attack occurring at the future time.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.