Patent ID: 11895034
Assignee: JOINESTY, INC.
Field: Digital communication (Electrical engineering)
Classification: CPC H | IPC H

Claim 9:
10. A system for selectively restricting access to traffic, the system comprising:
a first one or more processors;
a training engine configured to execute on the first one or more processors, the training engine further configured to generate a machine learning (ML) model by:
A) acquiring a plurality of instances of historical traffic (i) originating from one or more servers each implementing a different service, and (ii) destined for one or more end-user devices, each instance of historical traffic including one or more fields; and
B) training the ML model using the plurality of instances to classify fields included in the plurality of instances into a plurality of categories of information;

a second one or more processors configured to receive the ML model from the first one or more processors via a communication network; and
an obfuscation engine configured to execute on the second one or more processors, the obfuscation engine further configured to implement the ML model by:
(i) receiving traffic from a server implementing a service, 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 of information 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 without restricting access to at least a portion of the traffic; and
(v) transmitting the modified traffic to the end-user device;

wherein the training engine is configured to acquire the plurality of instances of historical traffic by:
acquiring a first set of instances of historical traffic originating from a first server, the first set of instances having a first format; and
acquiring a second set of instances of historical traffic originating from a second server, the second set of instances having a second format; and
wherein the training engine is further configured to train the ML model by:
training the ML model to identify the first set of instances having the first format and the second set of instances having the second format;
training the ML model to classify fields included in the first set of instances into the plurality of categories; and
training the ML model to classify fields included in the second set of instances into the plurality of categories.