System and method for network address anomaly detection using machine learning
US12177232B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Apr 5, 2022 |
| Grant date | Dec 24, 2024 |
| Priority date | — |
| Expiry date | Feb 2, 2043 |
Classification
- Technology area (CPC H)Electricity
- CPC primaryH04L63/1466
- WIPO fieldDigital communication
- WIPO sectorElectrical engineering
Abstract
Embodiments of the invention are directed to systems, methods, and computer program products for utilizing machine learning to predict future deceitful domain names and determine preferred security responses. As such, the system allows for use of a machine learning engine to collect new domain name registration information from a plurality of sources and predict future name registrations associated with said sources. A single user may register deceitful domain names through a plurality of domain name registration systems. By collecting data from multiple servers, the system may identify data trends and generate predictions of future domain names independently of any individual server. Thus, the system may benefit a number of entities, by providing real-time data analysis that would not be obtainable by any one entity operating alone. Additionally, the system may provide a single managing entity with real-time suggestions that may decrease the likelihood of a security incident involving a particular domain name.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.