Training and implementing a machine learning model to selectively restrict access to traffic
US11895034B1 · kind B1 · utility
Assignee
Inventors
Key dates
| Filing date | May 28, 2021 |
| Grant date | Feb 6, 2024 |
| Priority date | — |
| Expiry date | Jul 22, 2041 |
Classification
- Technology area (CPC H)Electricity
- CPC primaryH04L63/20
- WIPO fieldDigital communication
- WIPO sectorElectrical engineering
Abstract
The disclosed systems and techniques enable selectively restricting access of an end-user device to traffic. An example method may include training a machine learning (ML) model using a plurality of instances of historical traffic to classify fields included in the plurality of instances into a plurality of categories of information. The method may further include implementing the ML model by: (i) receiving traffic from a server, the traffic responsive to a request from an end-user device; (ii) identifying a field included in the traffic that corresponds to a category of the plurality of categories by applying the ML model to the traffic; (iii) in response to identifying that the field corresponds to the category, selecting a rule corresponding to the category; (iv) modifying the traffic in accordance with the rule to restrict access to information in the field; and (v) transmitting the modified traffic to the end-user device.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.