Risk assessment for network access control through data analytics
US12047392B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Apr 28, 2021 |
| Grant date | Jul 23, 2024 |
| Priority date | — |
| Expiry date | Sep 14, 2041 |
Classification
- Technology area (CPC H)Electricity
- CPC primaryH04L63/205
- WIPO fieldDigital communication
- WIPO sectorElectrical engineering
Abstract
Methods and systems of risk assessment for network access control through data analytics. An embodiment of the invention employs well-known machine-learning clustering methods to learn normal entity behavior by looking for patterns in the events that stream in continuously. In an embodiment of the invention, normal entity behaviors are represented as clusters of event vectors. An embodiment of the invention evaluates the risk level for a new event of an entity by comparing the event with the entity's profile represented as clusters of event vectors. In an embodiment of the invention, the risk level is associated with a confidence level. Confidence level indicates how well the system knows about the entity. Embodiments of the invention do not need human administration in the process of building entity profile and assessing risk level of events associated with an entity.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.