Cybersecurity detection and mitigation system using machine learning and advanced data correlation
US11297078B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Feb 28, 2019 |
| Grant date | Apr 5, 2022 |
| Priority date | — |
| Expiry date | Jun 12, 2040 |
Classification
- Technology area (CPC H)Electricity
- CPC primaryH04L63/102
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Computer system security is often implemented using rules-based systems (e.g., allow traffic to this network port, deny it for those network ports; user A is allowed access to these files, but not those files). In enterprises, multiple such systems may be deployed, but fail to be able to intelligently handle anomalies that may technically be permissible but in reality represents a high possibility that there is an underlying threat or problem. The present disclosure describes the ability to build adaptive models using machine learning techniques that integrate data from multiple different domains (e.g. user identity domain, system device domain) and allow for automated decision making and mitigation actions that can provide greater effectiveness than previous systems allowed.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.