| CPC G06F 21/6218 (2013.01) [G06F 16/27 (2019.01); G06F 21/1011 (2023.08); G06F 21/1014 (2023.08); G06F 21/1015 (2023.08); G06F 21/32 (2013.01); G06F 21/64 (2013.01); H04L 63/10 (2013.01); G06Q 20/065 (2013.01); G06Q 20/326 (2020.05); G06Q 20/40 (2013.01); H04L 9/3231 (2013.01); H04L 63/083 (2013.01); H04L 63/0861 (2013.01)] | 17 Claims |
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1. A method for generating dynamic non-fungible tokens, comprising:
receiving an authentication request for a transaction from at least one device associated with a user;
collecting, via one or more data mining applications or web-crawling applications, identification data associated with the at least one device or the user from one or more databases;
processing, via a machine learning model, the identification data associated with the at least one device or the user to generate the dynamic non-fungible tokens;
storing, via the machine learning model, the dynamic non-fungible tokens in a transaction block of a distributed blockchain; and
transmitting the dynamic non-fungible tokens to a digital wallet application to authenticate the transaction, wherein the dynamic non-fungible tokens is transmitted from a first digital wallet application associated with the user to a second digital wallet application with a service provider,
wherein a supervised learning is utilized to train the machine learning model, the supervised learning including:
inputting, in real-time or near real-time, training data into the machine learning model for generating the dynamic non-fungible tokens for storage into the distributed blockchain, wherein the training data includes an input and a correct output;
monitoring, in real-time or near real-time, accuracy of the machine learning model through a loss function; and
adjusting the machine learning model until an identified error is minimized.
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