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:
Jul. 30, 2024

Filed:

Oct. 25, 2022
Applicant:

Wells Fargo Bank, N.a., San Francisco, CA (US);

Inventors:

Lawrence T. Belton, Jr., Charlotte, NC (US);

Jon M. Welborn, Winston Salem, NC (US);

Gary Simms, Sr., Manassas, VA (US);

Peter Anatole Makohon, Huntersville, NC (US);

Jacob Lee, San Francisco, CA (US);

Assignee:

Wells Fargo Bank, N.A., San Francisco, CA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
H04L 29/06 (2006.01); G06F 18/214 (2023.01); G06N 5/02 (2023.01); G06N 20/00 (2019.01); H04L 9/40 (2022.01);
U.S. Cl.
CPC ...
H04L 63/1433 (2013.01); G06F 18/214 (2023.01); G06N 5/02 (2013.01); G06N 20/00 (2019.01); H04L 63/1425 (2013.01); H04L 63/20 (2013.01);
Abstract

The innovation disclosed and claimed herein, in one aspect thereof, comprises systems and methods of autonomous asset configuration modeling and management. The innovation includes probing elements of a networked architecture to compile information about elements in the networked architecture. The innovation learns a configuration for the at least one element in the environment based on the probing and determines vulnerabilities in the learned configuration. The innovation develops a threat model based on the learned configuration. The innovation applies the threat model to the elements of the networked architecture and deploys a configuration that resolves the vulnerabilities based on the threat model to the elements in the networked architecture. The threat model can be developed over time using machine learning concepts and deep learning of data sources associated with the elements and vulnerabilities.


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