US 12,332,976 B2
Blockchain encoding system
Logan A. Wells, Lewes, DE (US); and Rick Anthony Wells, Lewes, DE (US)
Assigned to Black Atom Technologies, Inc., Lewes, DE (US)
Filed by Black Atom Technologies, Inc., Lewes, DE (US)
Filed on Apr. 17, 2024, as Appl. No. 18/637,848.
Application 18/637,848 is a continuation of application No. 18/352,113, filed on Jul. 13, 2023, granted, now 11,989,267.
Claims priority of provisional application 63/373,818, filed on Aug. 29, 2022.
Prior Publication US 2024/0403391 A1, Dec. 5, 2024
This patent is subject to a terminal disclaimer.
Int. Cl. H04L 9/40 (2022.01); G06F 21/10 (2013.01); G06N 20/00 (2019.01); H04L 9/00 (2022.01); H04L 9/32 (2006.01)
CPC G06F 21/1014 (2023.08) [G06N 20/00 (2019.01); H04L 9/3213 (2013.01); H04L 9/50 (2022.05)] 23 Claims
OG exemplary drawing
 
1. A computer-implemented method of securely controlling an electronic asset, the method comprising:
evaluating an ownership status of the electronic asset;
responsive to the evaluating, binding an asset non-fungible token (NFT) with at least one of: (i) a representation of an identity of an owner node paired with the electronic asset and (ii) a representation of an identity of an authorized user node paired with the electronic asset, the asset NFT pertaining to the electronic asset;
registering the bound at least one representation of the identity and the asset NFT on a blockchain associated with the electronic asset;
computationally performing a task involving the electronic asset, and the bound at least one representation of the identity, in response to receiving a task request from at least one of the owner node and the authorized user node and securely controlling the electronic asset;
configuring a scoring engine to track a computational value pertaining to the electronic asset, the computational value corresponding to at least one of: (i) a score associated with the owner node or the authorized user node, (ii) a worth of the electronic asset, and (iii) a risk level associated with the performing of the task involving the electronic asset;
in an event the computational value corresponds to the worth of the electronic asset, configuring an artificial intelligence (AI) module to train a model for the computational value based upon descriptive data relating to the electronic asset; and
in an event the computational value corresponds to the score associated with the owner node or the authorized user node, configuring the artificial intelligence (AI) module to train a model for the computational value based upon behavioral data.