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

Claim 7:
8. The method of claim 7, wherein the training data is first training data, the method further comprising:
generating a first trained machine learning model based on the first training data, wherein the first training data comprises information pertaining to characteristics of upload activity performed at a plurality of client devices associated with a plurality of users;
retraining the first trained machine learning model using user-specific information pertaining to user-specific characteristics of upload activity performed at a third client device, the method comprising:
generating second training data to retrain the first trained machine learning model to create a user-specific trained machine learning model, wherein generating the second training data comprises:
generating fifth training input, the fifth training input comprising (i) information identifying fifth amounts of data uploaded during a fifth specified time interval for the plurality of application categories, and (ii) information identifying fifth locations external to the third client device to which the fifth amounts of data are uploaded; and
generating a fifth target output for the fifth training input, wherein the fifth target output indicates whether the fifth amounts of data uploaded to the fifth locations correspond to the malicious or the non-malicious upload activity; and
providing the second training data to retrain the first trained machine learning model on (i) a new set of training inputs comprising the fifth training input, and (ii) a new set of target outputs comprising the fifth target output.