Apparatus and methods for verifying lost user data
Aspects relate to apparatuses and methods for using machine learning to verify lost user data in a resource data storage system. An exemplary apparatus includes a processor and a memory communicatively connected to the processor, the memory containing instructions configuring the processor to identify a plurality of lost user data stored in a resource data storage system potentially associated with a particular user of a plurality of users, verify, using a recovery program, the plurality of lost user data potentially associated with the particular user and link, as a function of the verification, the plurality of lost user data to the particular user.
1. An apparatus for using machine learning to verify lost user data in a resource data storage
system, the apparatus comprising:
at least a processor; and
a memory communicatively connected to the processor, the memory containing instructions configuring the at least a processor to:
identify a plurality of lost user data stored in a resource data storage system potentially associated with a particular user of a plurality of users, the resource data storage system stored on an immutable sequential listing, wherein identifying a plurality of lost user data comprises dividing the plurality of lost user data into a plurality of user identifier subsets that are identified by at least a public key, wherein each of the plurality of user identifier subsets is matched with the particular user of the plurality of users;
verify, using a recovery program, the plurality of lost user data potentially associated with the particular user and;
link, as a function of the verification, the plurality of lost user data to the particular user.
2. The apparatus of claim 1 , wherein the immutable sequential listing includes a cryptographic accumulator.
3. The apparatus of claim 1 , wherein the plurality of lost user data comprises a plurality of orphan blocks in a cryptographic hash chain existing outside of a main hash chain on the immutable sequential listing.
4. The apparatus of claim 1 , wherein dividing the plurality of lost user data into user identifier subsets comprises using a machine learning process to output data bins of matched lost user data to a particular user.
5. The apparatus of claim 4 , wherein the machine learning process includes using a classification algorithm.
6. The apparatus of claim 1 , wherein the recovery program comprises using public-key cryptography.
7. The apparatus of claim 1 , wherein verifying the plurality of lost user data comprises using fuzzy set comparison.
8. The apparatus of claim 1 , wherein verifying the plurality of lost user data comprises using proof of possession.
9. The apparatus of claim 8 , wherein verifying the plurality of lost user data comprises using a cryptographic commitment.
10. The apparatus of claim 3 , wherein linking the plurality of lost user data further comprises cryptographically inserting into the main hash-chain on the immutable sequential listing, the plurality of lost user data associated with the particular user.
11. A method for using machine learning to verify lost user data in a resource data storage system, the method comprising:
identifying, using a computing device, a plurality of lost user data stored in a resource data storage system potentially associated with a particular user of a plurality of users, the resource data storage system stored on an immutable sequential listing, wherein identifying a plurality of lost user data comprises dividing the plurality of lost user data into a plurality of user identifier subsets that are identified by at least a public key, wherein each of the plurality of user identifier subsets is matched with the particular user of the plurality of users;
verifying, using a recovery program and a computing device, the plurality of lost user data potentially associated with the particular user and;
linking, using a computing device, as a function of the verification, the plurality of lost user data to the particular user.
12. The method of claim 11 , wherein the immutable sequential listing includes a cryptographic accumulator.
13. The method of claim 11 , wherein the plurality of lost user data comprises a plurality of orphan blocks in a cryptographic hash chain existing outside of a main hash chain on the immutable sequential listing.
14. The method of claim 11 , wherein dividing the plurality of lost user data into user identifier subsets comprises using a machine learning process to output data bins of matched lost user data to a particular user.
15. The method of claim 14 , wherein the machine learning process includes using a classification algorithm.
16. The method of claim 11 , wherein the recovery program comprises using public-key cryptography.
17. The method of claim 11 , wherein verifying the plurality of lost user data comprises using fuzzy set comparison.
18. The method of claim 11 , wherein verifying the plurality of lost user data comprises using proof of possession.
19. The method of claim 18 , wherein verifying the plurality of lost user data comprises using a cryptographic commitment.
20. The method of claim 13 , wherein linking the plurality of lost user data further comprises cryptographically inserting into the main hash-chain on the immutable sequential listing, the plurality of lost user data associated with the particular user.