Method and system for generating synthetic feature vectors from real, labelled feature vectors in artificial intelligence training of a big data machine to defend
US10848508B2 · kind B2 · utility
Inventors
Key dates
| Filing date | May 21, 2018 |
| Grant date | Nov 24, 2020 |
| Priority date | — |
| Expiry date | Nov 30, 2038 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06F18/217
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Identifying and detecting threats to an enterprise system groups log lines from enterprise data sources and/or from incoming data traffic. The process applies artificial intelligence processing to the statistical outlier in the event of the statistical outliers comprises a sparsely labelled real data set, by receiving the sparsely labelled real data set for identifying malicious data and comprising real labelled feature vectors and generating a synthetic data set comprising a plurality of synthetic feature vectors derived from the real, labelled feature vectors. The process further identifies the sparsely labelled real data set as a local data set and the synthetic data set as a global set. The process further applies a transfer learning framework for mixing the global data set with the local data set for increasing the precision recall area under curve (PR AUC) for reducing false positive indications occurring in analysis of the threats to the enterprise.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.