System and method for surfacing cyber-security threats with a self-learning recommendation engine
US11637862B1 · kind B1 · utility
Assignee
Inventor
Key dates
| Filing date | Sep 30, 2019 |
| Grant date | Apr 25, 2023 |
| Priority date | — |
| Expiry date | Aug 21, 2041 |
Classification
- Technology area (CPC H)Electricity
- CPC primaryH04L63/1433
- WIPO fieldDigital communication
- WIPO sectorElectrical engineering
Abstract
Techniques for performing cyber-security alert analysis and prioritization according to machine learning employing a predictive model to implement a self-learning feedback loop. The system implements a method generating the predictive model associated with alert classifications and/or actions which automatically generated, or manually selected by cyber-security analysts. The predictive model is used to determine a priority for display to the cyber-security analyst and to obtain the input of the cyber-security analyst to improve the predictive model. Thereby the method implements a self-learning feedback loop to receive cyber-security alerts and mitigate the cyberthreats represented in the cybersecurity alerts.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.