US 12,261,873 B2
Augmented and virtual reality security planner
Michael Young, Davidson, NC (US); Anthony D. Lange, Washington, DC (US); Tarsha Salley, Charlotte, NC (US); Joshua Shi, Chicago, IL (US); Madeline Deneen Fest, Charlotte, NC (US); Adam King, Fort Mill, SC (US); and Henrry Batista, Chicago, IL (US)
Assigned to Bank of America Corporation, Charlotte, NC (US)
Filed by Bank of America Corporation, Charlotte, NC (US)
Filed on Mar. 30, 2023, as Appl. No. 18/128,440.
Prior Publication US 2024/0333744 A1, Oct. 3, 2024
Int. Cl. H04L 9/40 (2022.01); G06F 21/57 (2013.01); G06T 19/00 (2011.01); H04L 41/02 (2022.01); H04L 41/0866 (2022.01); H04L 41/22 (2022.01); H04L 43/045 (2022.01)
CPC H04L 63/1433 (2013.01) [G06F 21/577 (2013.01); H04L 41/22 (2013.01); H04L 43/045 (2013.01); H04L 63/20 (2013.01); G06T 19/006 (2013.01); H04L 41/024 (2013.01); H04L 41/0866 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A method for virtual network augmentation, the method comprising:
inputting network architecture data into a network augmentation system, said network architecture data corresponding to a network, said network architecture data comprising:
a plurality of physical network component images;
a plurality of digital network systems maps;
a plurality of digital network configurations maps;
a plurality digital images that correspond to network systems physical maps; and
a plurality of digital images that correspond to network configurations physical maps;
retrieving, from a public database, data relating to cybersecurity standards;
retrieving, from a public database, data relating to network security standards;
retrieving, from a public database, publicly stored data relating to standard network vulnerabilities;
retrieving, from a private database, privately stored data relating to historical vulnerabilities, said historical vulnerabilities having occurred within the network;
rendering a three-dimensional map of the network using the network architecture data;
displaying the three-dimensional map on an interactive display module;
identifying one or more security vulnerabilities applicable to the network based on the data relating to cybersecurity standards, the data relating to network security standards, the publicly stored data, and the privately stored data;
mapping the one or more identified security vulnerabilities as an overlay to the three-dimensional map;
prioritizing the one or more identified security vulnerabilities in a priority list based on metadata associated with the publicly stored data and privately stored data;
selecting a first number of identified security vulnerabilities from the priority list;
identifying, using an artificial intelligence module, one or more network solutions for each of the selected vulnerabilities;
layering the one or more network solutions at network locations that correspond to the selected vulnerabilities on the three-dimensional map;
forecasting, within the three-dimensional map, one or more ways the network will be affected in response to the one or more network solutions;
selecting through the display module, a first solution from the one or more solutions for implementation;
outputting the first solution to an implementation module; and
implementing the first solution using the implementation module.