US 12,267,335 B2
Self-training classification
Siying Yang, Cupertino, CA (US); and Yang Zhang, Fremont, CA (US)
Assigned to Forescout Technologies, Inc., San Jose, CA (US)
Filed by FORESCOUT TECHNOLOGIES, INC., San Jose, CA (US)
Filed on Feb. 15, 2024, as Appl. No. 18/443,098.
Application 18/443,098 is a continuation of application No. 17/729,997, filed on Apr. 26, 2022, granted, now 11,936,660.
Application 17/729,997 is a continuation of application No. 17/024,469, filed on Sep. 17, 2020, granted, now 11,343,149, issued on May 24, 2022.
Application 17/024,469 is a continuation of application No. 16/023,413, filed on Jun. 29, 2018, granted, now 10,812,334, issued on Oct. 20, 2020.
Prior Publication US 2024/0195815 A1, Jun. 13, 2024
This patent is subject to a terminal disclaimer.
Int. Cl. H04L 9/40 (2022.01); G06F 18/24 (2023.01); G06N 20/00 (2019.01); H04L 41/0853 (2022.01); H04L 43/04 (2022.01); H04L 43/10 (2022.01)
CPC H04L 63/14 (2013.01) [G06F 18/24 (2023.01); G06N 20/00 (2019.01); H04L 41/0853 (2013.01); H04L 43/04 (2013.01); H04L 43/10 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A method comprising:
accessing a plurality of device classification methods, wherein each of the plurality of methods has a respective associated model, and wherein each of the plurality of methods has a respective associated reliability level in classifying a device type or a device model of a plurality of devices communicatively coupled to a network;
generating, by a processing device, a respective data set associated with each of the device classification methods based on classifying the device type or the device model of the plurality of devices communicatively coupled to the network; and
selecting a first device classification method and a second device classification method of the plurality of device classification methods, wherein the first device classification method has a higher reliability level than the second device classification method.