Patent ID: 11936670
Assignee: SEQUOIA BENEFITS AND INSURANCE SERVICES, LLC
Field: Computer technology (Electrical engineering)
Classification: CPC G  H | IPC G  H

Claim 0:
1. A method for training a machine learning model using information pertaining to characteristics of upload activity performed at a client device, the method comprising:
generating, by a processing device, training data to train the machine learning model, wherein generating the training data comprises:
generating first training input, the first training input comprising (i) information identifying, for each of a plurality of application categories, data categories pertaining to first amounts of data uploaded from the client device during a specified time interval, wherein each of the plurality of application categories comprise one or more applications that are installed at the client device and that upload the first amounts of data; and
generating a first target output for the first training input, wherein the first target output indicates whether the data categories corresponding to the first amounts of data correspond to malicious or non-malicious upload activity; and

providing the training data to train the machine learning model on (i) a set of training inputs comprising the first training input, and (ii) a set of target outputs comprising the first target output.