Systems and methods configuring a subscriber-specific ensemble of machine learning models
US10491617B1 · kind B1 · utility
Assignee
Inventors
Key dates
| Filing date | May 31, 2019 |
| Grant date | Nov 26, 2019 |
| Priority date | — |
| Expiry date | May 31, 2039 |
Classification
- Technology area (CPC H)Electricity
- CPC primaryH04L63/1416
- WIPO fieldDigital communication
- WIPO sectorElectrical engineering
Abstract
A machine learning-based system and method for identifying digital threats that includes implementing a machine learning-based digital threat mitigation service over a distributed network of computers; constructing, by the machine learning-based digital threat mitigation service, a subscriber-specific machine learning ensemble that includes a plurality of distinct machine learning models, wherein each of the plurality of distinct machine learning models is configured to perform a distinct machine learning task for identifying a digital threat or digital fraud; constructing a corpus of subscriber-specific digital activity data for training the plurality of distinct machine learning models of the subscriber-specific ensemble; training the subscriber-specific ensemble using at least the corpus of subscriber-specific digital activity data; and deploying the subscriber-specific ensemble.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.