US 12,204,649 B2
Security assessment platform
Andrew Charles Storms, San Francisco, CA (US); and Daniel C. Riedel, San Francisco, CA (US)
Assigned to Copado, Inc., Chicago, IL (US)
Appl. No. 16/969,663
Filed by Copado, Inc., Chicago, IL (US)
PCT Filed Feb. 13, 2019, PCT No. PCT/US2019/017774
§ 371(c)(1), (2) Date Aug. 13, 2020,
PCT Pub. No. WO2019/160905, PCT Pub. Date Aug. 22, 2019.
Claims priority of provisional application 62/630,482, filed on Feb. 14, 2018.
Prior Publication US 2020/0401703 A1, Dec. 24, 2020
Int. Cl. G06F 21/57 (2013.01); G06F 9/48 (2006.01); G06F 11/34 (2006.01); G06N 20/00 (2019.01)
CPC G06F 21/577 (2013.01) [G06F 9/485 (2013.01); G06F 11/3409 (2013.01); G06N 20/00 (2019.01); G06F 2221/034 (2013.01)] 26 Claims
OG exemplary drawing
 
1. A computer-implemented method performed by at least one processor, the method comprising:
receiving, by the at least one processor, input data that is provided through an assessment platform;
analyzing, by the at least one processor, the input data to generate one or more metrics that each provide a measurement of an operational aspect of an organization, wherein the one or more metrics include one or more metrics that provide an assessment of a software or system development lifecycle (SDLC);
generating, by the at least one processor, one or more tasks based on one or more of the input data and the one or more metrics; and
presenting, by the at least one processor, the one or more metrics and the one or more tasks through a user interface (UI) of the assessment platform; and
wherein the analyzing of the input data employs at least one machine learning technique, wherein the at least one machine learning technique comprises a trained machine learning classifier that predicts one or more of the one or more metrics based on the input data, wherein the trained machine learning classifier is trained using labeled training data that indicates a metric corresponding to one or more values within a set, subset, or element of the labeled training data.