US 12,147,512 B2
Generating authentication template filters using one or more machine-learned models
William Charles Suski, Mount Pleasant, SC (US)
Assigned to Applied Engineering Concepts, Inc., Eldersburg, MD (US)
Filed by Applied Engineering Concepts, Inc., Eldersburg, MD (US)
Filed on May 27, 2022, as Appl. No. 17/826,654.
Claims priority of provisional application 63/227,712, filed on Jul. 30, 2021.
Prior Publication US 2023/0035291 A1, Feb. 2, 2023
Int. Cl. G06F 21/31 (2013.01); G06N 20/00 (2019.01)
CPC G06F 21/31 (2013.01) [G06N 20/00 (2019.01)] 18 Claims
OG exemplary drawing
 
1. A computer-implemented method, the method comprising:
obtaining, by a computing system comprising one or more processors, a trained authentication model, wherein the trained authentication model is trained to classify a computing device based on signal data;
determining, by the computing system, an input that the trained authentication model classifies as an authenticated class, wherein the authenticated class is descriptive of authenticated signal data associated with an authenticated computing device, wherein determining, by the computing system, the input that the trained authentication model classifies as the authenticated class comprises: generating, by the computing system, example signal data with an input model, wherein the input model is trained by:
generating, by the computing system, training signal data with the input model;
processing, by the computing system, the training signal data with the trained authentication model to generate an authentication classification;
evaluating, by the computing system, a loss function that evaluates a difference between the authentication classification and the authentication class; and
adjusting, by the computing system, one or more parameters of the input model based at least in part on the loss function;
generating, by the computing system, an authentication filter based on the input; and
storing, by the computing system, the authentication filter for classification.