US 12,147,582 B2
Validation based authenticated storage in distributed ledger
Vaibhav Shah, Pune (IN); Hirendra Singh Parihar, Indore (IN); Nikhil Prakash Bhandari, Pune (IN); Ankit Gupta, Phursungi (IN); Akif Alam Khan, Aurangabad (IN); Anu Saxena, Uttarakhand (IN); Ramesh Peetha, Guntur (IN); and Shabbar Ali Ghadiyali, Banswara (IN)
Assigned to ACCENTURE GLOBAL SOLUTIONS LIMITED, Dublin (IE)
Filed by ACCENTURE GLOBAL SOLUTIONS LIMITED, Dublin (IE)
Filed on Mar. 24, 2022, as Appl. No. 17/703,788.
Prior Publication US 2023/0306139 A1, Sep. 28, 2023
Int. Cl. G06F 21/64 (2013.01); G06F 16/215 (2019.01); G06F 16/27 (2019.01); H04L 9/40 (2022.01)
CPC G06F 21/64 (2013.01) [G06F 16/215 (2019.01); G06F 16/27 (2019.01); H04L 63/08 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A system comprising:
a processor coupled with a memory, wherein the memory stores instructions to be executed by the processor:
a data validator implemented via the processor to:
receive an input dataset comprising a component metadata, wherein the component metadata includes information pertaining to a feature corresponding to each component of a plurality of components associated with a product or a service;
perform, using a validation model and through a rules engine, validation of the information in the component metadata to obtain a validation dataset, wherein the validation is performed by assessing the feature with respect to a corresponding pre-defined rule stored in the rules engine, and wherein the validation enables to predict at least one invalid feature in the component dataset; and
an insight generator implemented via the processor to:
generate, based on the validation datasets, automated insights pertaining to mitigation of the at least one invalid feature;
wherein the automated insights are stored in a distributed ledger to facilitate an authenticated storage of the automated insights, and wherein the authenticated storage is facilitated by a network comprising a plurality of nodes.