The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Jan. 17, 2023

Filed:

Nov. 24, 2020
Applicant:

Kyndryl, Inc., New York, NY (US);

Inventors:

Fabio Zanforlin Zaina, Campinas, BR;

Leonardo de Bem Ferreira, Campinas, BR;

Silvana Galeazzi, Campinas, BR;

Marco Antonio Milanez, Piracicaba, BR;

Sergio Varga, Campinas, BR;

Thiago Bianchi, Sao Carlos, BR;

Assignee:

KYNDRYL, INC., New York, NY (US);

Attorneys:
Primary Examiner:
Int. Cl.
CPC ...
G06F 8/65 (2018.01); G06N 3/08 (2006.01); G06F 16/245 (2019.01); G06N 3/04 (2006.01); G06F 21/57 (2013.01); G06N 20/10 (2019.01);
U.S. Cl.
CPC ...
G06F 8/65 (2013.01); G06F 16/245 (2019.01); G06F 21/57 (2013.01); G06N 3/0445 (2013.01); G06N 3/08 (2013.01); G06N 20/10 (2019.01); G06F 21/577 (2013.01); G06F 2221/033 (2013.01);
Abstract

A method and a system for automating security updates in a multi-tiered architecture of a system environment. The method includes receiving a software update note relating to a multi-tiered architecture system environment and determining a patch in the software update note is initially compatible with the system environment. The method also includes predicting, by a patch acceptance machine learning model, the patch is patchable within the system environment and predicting, by an installation machine learning model, an installation patch time for the patch on the system environment. The method also includes installing the patch at the installation patch time on the system environment, and validating the patch installation using a validation machine learning model.


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