	US 12,348,552 B2
	Automated prediction of cyber-security attack techniques using knowledge mesh
Gal Engelberg, Pardes-hana (IL); Dan Klein, Rosh HaAyim (IL); Moshe Hadad, Rosh HaAyim (IL); and Hodaya Binyamini, Beer Sheva (IL)
Assigned to Accenture Global Solutions Limited, Dublin (IE)
Filed by Accenture Global Solutions Limited, Dublin (IE)
Filed on Jun. 15, 2023, as Appl. No. 18/335,305.
Claims priority of provisional application 63/410,698, filed on Sep. 28, 2022.
Claims priority of provisional application 63/352,471, filed on Jun. 15, 2022.
Prior Publication US 2023/0412634 A1, Dec. 21, 2023
Int. Cl. H04L 9/40 (2022.01); G06N 5/04 (2023.01); H04L 41/02 (2022.01); H04L 41/16 (2022.01)

CPC H04L 63/1433 (2013.01) [G06N 5/04 (2013.01); H04L 41/024 (2013.01); H04L 41/16 (2013.01)]

20 Claims

1. A computer-implemented method for reducing cyber-security risk, comprising:

selecting one or more modules for inclusion in a knowledge mesh, wherein each module is associated with a respective aspect and maintains a knowledge graph specific to the respective aspect, wherein each knowledge graph is generated using data from one or more cyber-security repositories and includes nodes and connections between the nodes;

receiving a query corresponding to a first node of a first knowledge graph included in the knowledge mesh;

generating a response to the query by identifying connections between the first node of the first knowledge graph and at least one node of at least one other knowledge graph included in the knowledge mesh; and

identifying, based on the response to the query, one or more actions to reduce cyber-security risk.