IP Library Granted Patent US 12,549,196
Granted Patent B2
US 12,549,196 · App. 18/643,252 · Granted Feb 10, 2026

Systems and methods for dynamically generating and mapping unicode for cross-distributed network data transmissions

Inventors: Sandeep Kumar Chauhan (Telangana, IN); Saurabh Arora (Haryana, IN)
Assignee: BANK OF AMERICA CORPORATION
H03M7/3066H03M7/705
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Quick Facts
Patent No.
US 12,549,196
App. No.
18/643,252
Granted
Feb 10, 2026
Kind
B2
Abstract

Systems, computer program products, and methods are described herein for generating and mapping unicode for cross-distributed network data transmissions. The present disclosure is configured to identify a cross-distributed network data transmission comprising source ledger code; generate a core schema for a destination ledger, wherein the destination ledger is based on data of the cross-distributed network data transmission; generate, by a ledger transformation module, a data dictionary, wherein the ledger transformation module receives ledger code from a large language model (LLM); generate code mapping instructions for the cross-distributed network data transmission based on the core schema for the destination ledger; convert the source ledger code to a unicode; receive, by a receiver schema mapping module, the unicode and the code mapping instructions; and generate, by the receiver schema mapping module, an intermediary ledger comprising the unicode and based on the code mapping instructions.

Claims (52)

1 . A system for dynamically generating and mapping Unicode for cross-distributed network data transmissions, the system comprising:

a processing device;

a non-transitory storage device containing instructions when executed by the processing device, causes the processing device to perform the steps of:

identify a cross-distributed network data transmission comprising source ledger code;

generate a core schema for a destination ledger, wherein the destination ledger is based on data of the cross-distributed network data transmission;

generate, by a ledger transformation module, a data dictionary, wherein the ledger transformation module receives ledger code from a large language model (LLM);

generate code mapping instructions for the cross-distributed network data transmission based on the core schema for the destination ledger;

convert the source ledger code to a unicode;

generate, by a receiver schema mapping module, an intermediary ledger comprising the unicode and based on the code mapping instructions; and

automatically convert the intermediary ledger to the destination ledger.

2 . The system of claim 1 , wherein the cross-distributed network data transmission is between a source ledger and the destination ledger, and wherein the source ledger and the destination ledger comprise different schemas.

3 . The system of claim 2 , wherein the processing device is further configured to perform the steps of:

determine whether a source ledger schema and a destination ledger schema are compatible.

4 . The system of claim 1 , wherein the processing device is further configured to perform the steps of:

determine whether the cross-distributed network data transmission is an internal data category or an external data category.

5 . The system of claim 4 , wherein in an instance where the cross-distributed network data transmission is the internal data category, and wherein the processing device is further configured to perform the steps of:

perform a local conversion of the source ledger code using the ledger transformation module comprising the code mapping instructions.

6 . The system of claim 1 , wherein the LLM comprises current data associated with a plurality of entity ledgers and different schemas.

7 . The system of claim 1 , wherein the intermediary ledger comprises an intermediary schema and the unicode that can be mapped to a destination schema and destination ledger code.

8 . A computer program product for automatically generating and implementing password rotations using artificial intelligence, the computer program product comprising a non-transitory computer-readable medium comprising code causing an apparatus to:

identify a cross-distributed network data transmission comprising source ledger code;

generate a core schema for a destination ledger, wherein the destination ledger is based on data of the cross-distributed network data transmission;

generate, by a ledger transformation module, a data dictionary, wherein the ledger transformation module receives ledger code from a large language model (LLM);

generate code mapping instructions for the cross-distributed network data transmission based on the core schema for the destination ledger;

convert the source ledger code to a unicode;

generate, by a receiver schema mapping module, an intermediary ledger comprising the unicode and based on the code mapping instructions; and

automatically convert the intermediary ledger to the destination ledger.

9 . The computer program product of claim 8 , wherein the cross-distributed network data transmission is between a source ledger and the destination ledger, and wherein the source ledger and the destination ledger comprise different schemas.

10 . The computer program product of claim 9 , wherein the code further causes the apparatus to

determine whether a source ledger schema and a destination ledger schema are compatible.

11 . The computer program product of claim 8 , wherein the code further causes the apparatus to:

determine whether the cross-distributed network data transmission is an internal data category or an external data category.

12 . The computer program product of claim 11 , wherein in an instance where the cross-distributed network data transmission is the internal data category, and wherein the processing device is further configured to perform the steps of:

perform a local conversion of the source ledger code using the ledger transformation module comprising the code mapping instructions.

13 . The computer program product of claim 8 , wherein the LLM comprises current data associated with a plurality of entity ledgers and different schemas.

14 . The computer program product of claim 8 , wherein the intermediary ledger comprises an intermediary schema and the unicode that can be mapped to a destination schema and destination ledger code.

15 . A computer-implemented method for automatically generating and implementing password rotations using artificial intelligence, the computer-implemented method comprising:

identifying a cross-distributed network data transmission comprising source ledger code;

generating a core schema for a destination ledger, wherein the destination ledger is based on data of the cross-distributed network data transmission;

generating, by a ledger transformation module, a data dictionary, wherein the ledger transformation module receives ledger code from a large language model (LLM);

generating code mapping instructions for the cross-distributed network data transmission based on the core schema for the destination ledger;

convert the source ledger code to a unicode;

generate, by a receiver schema mapping module, an intermediary ledger comprising the unicode and based on the code mapping instructions; and

automatically converting the intermediary ledger to the destination ledger.

16 . The computer-implemented method of claim 15 , wherein the cross-distributed network data transmission is between a source ledger and the destination ledger, and wherein the source ledger and the destination ledger comprise different schemas.

17 . The computer-implemented method of claim 16 , further comprising:

determining whether a source ledger schema and a destination ledger schema are compatible.

18 . The computer-implemented method of claim 15 , further comprising:

determining whether the data transmission exchange is an internal data category or an external data category.

19 . The computer-implemented method of claim 18 , wherein in an instance where the cross-distributed network data transmission is the internal data category, and wherein the computer-implemented method further comprises:

performing a local conversion of the source ledger code using the ledger transformation module comprising the code mapping instructions.

20 . The computer-implemented method of claim 15 , wherein the LLM comprises current data associated with a plurality of entity ledgers and different schemas.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Apr 23, 2024
From: CHAUHAN, SANDEEP KUMAR; ARORA, SAURABH
To: BANK OF AMERICA CORPORATION
Reel/Frame 067195/0466 →
Continuity (1)
Related Publication 20250330197A1 · Oct 23, 2025
References Cited (32)
US 5793381A · Edberg · 1998 [cited by examiner]
US 7086004B2 · Atkin · 2006 [cited by examiner]
US 7251667B2 · Atkin · 2007 [cited by examiner]
US 7278100B1 · Ehrman · 2007 [cited by examiner]
US 7940273B2 · Gurcan · 2011 [cited by examiner]
US 7999705B2 · Schneider · 2011 [cited by examiner]
US 10671315B2 · Sanghvi · 2020 [cited by applicant]
US 10713239B2 · Qiu · 2020 [cited by applicant]
US 10924264B2 · Wilson · 2021 [cited by applicant]
US 10938548B2 · Mercuri · 2021 [cited by applicant]
US 10956075B2 · Kursun · 2021 [cited by applicant]
US 11032293B2 · Biyani · 2021 [cited by applicant]
US 11126683B2 · Lu · 2021 [cited by applicant]
US 11128528B2 · Nolan · 2021 [cited by applicant]
US 11159620B2 · Wang · 2021 [cited by applicant]
US 11449476B2 · Oberhofer · 2022 [cited by applicant]
US 11481509B1 · Prasad · 2022 [cited by applicant]
US 11848939B2 · Biyani · 2023 [cited by applicant]
US 12010244B2 · Androulaki · 2024 [cited by applicant]
US 20020052902A1 · Bauer · 2002 [cited by examiner]
US 20040006569A1 · Carlin · 2004 [cited by examiner]
US 20040237046A1 · Burchall · 2004 [cited by examiner]
US 20070115488A1 · Engelman · 2007 [cited by examiner]
US 20090055395A1 · Jenks · 2009 [cited by examiner]
US 20110129086A1 · Schneider · 2011 [cited by examiner]
US 20170243193A1 · Manian · 2017 [cited by applicant]
US 20180025435A1 · Karame · 2018 [cited by applicant]
US 20180165476A1 · Carey · 2018 [cited by applicant]
US 20200336542A1 · Wang · 2020 [cited by applicant]
US 20220200973A1 · Tola · 2022 [cited by applicant]
CN 111191286B · 2020 [cited by applicant]
CN 108595157B · 2022 [cited by applicant]