System and method for data compaction and security with extended functionality

Patent metadata

Field	Value
Publication number	US-12489459-B2
Application number	US-202318478777-A
Country	US
Kind code	B2
Filing date	Sep 29, 2023
Priority date	Oct 30, 2017
Publication date	Dec 2, 2025
Grant date	Dec 2, 2025

Abstract

A system and method for scriptable selective obfuscation of records comprising a data obfuscation module configured to identify and perform data anonymization on personal identifiable information (PII) contained within a plurality of records to create a partially-blurred dataset, and further comprising an encoder which receives the partially-blurred dataset and performs data compaction on the partially-blurred dataset before storing the compacted dataset in a data storage system. In some implementations, the data storage system is a blockchain database and the system functions as a clearinghouse to validate and monitor transactions involving data access rights between record owners and third-party entities. The system can further broker such transactions and direct payment form the third-party entity to the record owner when access rights have been purchased.

First claim

What is claimed is:

1 . A system for scriptable selective obfuscation of records, comprising:
a computing device comprising a processor and a memory; an encoder comprising a first plurality of programming instructions stored in the memory which, when operating on the processor, causes the computing device to:
receive a record of information;
identify and obfuscate personally identifiable information (PII) within the record of information to create a partially-blurred dataset;
deconstruct the partially-blurred dataset into a plurality of sourceblocks;
generate and store an obfuscation dictionary, the obfuscation dictionary comprising a plurality of entries, each entry including:
an obfuscated token that replaces a specific instance of PII in the partially-blurred dataset; and
a corresponding sourceblock from the record of information prior to obfuscation, the sourceblock containing unmodified PII that was replaced by the obfuscated token;

encode the plurality of sourceblocks by generating a codebook, wherein the codebook is integrated with a script configured to decode encoded data associated with the obfuscated PII; and
store the encoded data and the codebook in a database.

2 . The system of claim 1 , further comprising a decoder comprising a second plurality of programming instructions stored in the memory which, when operating on the processor, causes the computing device to:
receive a request for one or more records of information, the request comprising parameters to be input into the script; retrieve the obfuscation dictionaries associated with requested one or more records based on the parameters; decode the encoded plurality of sourceblocks using the codebook to reconstruct the partially-blurred dataset; use the retrieved obfuscation dictionaries to restore the partially-blurred dataset to the original record; and return the de-blurred record to a requestor.

3 . The system of claim 1 , wherein the database is a blockchain database.

4 . The system of claim 1 , wherein the PII is obfuscated by replacing identified PII with unique nonces.

5 . The system of claim 4 , wherein the obfuscation dictionary is a nonce-to-original sourceblock dictionary.

6 . The system of claim 2 , wherein the parameters include a range of records to be decoded.

7 . The system of claim 6 , wherein the range of records comprises unique transaction identifiers for each record in the range of records.

8 . The system of claim 2 , wherein the requestor purchases access rights to one or more records of information.

9 . A method for scriptable selective obfuscation of records, comprising the steps of:
receiving, at a computing device, a record of information; identifying and generating, using an encoder operating on the computing device, personally identifiable information (PII) within the record of information to create a partially-blurred dataset; deconstructing, using the encoder, the partially-blurred dataset into a plurality of sourceblocks; generating and storing an obfuscation dictionary, the obfuscation dictionary comprising a plurality of entries, each entry including:
an obfuscated token that replaces a specific instance of PII in the partially-blurred dataset; and
a corresponding sourceblock from the record of information prior to obfuscation, the sourceblock containing unmodified PII that was replaced by the obfuscated token;
encoding, using the encoder, the plurality of sourceblocks by generating a codebook, wherein the codebook is integrated with a script configured to decode encoded data associated with the obfuscated PII; and storing, using the encoder, the encoded data and the codebook in a database.

10 . The method of claim 9 , further comprising the steps of:
receiving, at a decoder operating on the same or different computing device, a request for one or more records of information, the request comprising parameters to be input into the script; retrieving, using the decoder, the obfuscation dictionaries associated with requested one or more records based on the parameters; decoding, using the decoder, the encoded plurality of sourceblocks using the codebook to reconstruct the partially-blurred dataset; using the retrieved obfuscation dictionaries, using a decoder, to restore the partially-blurred dataset to the original record; and returning the de-blurred record to a requestor.

11 . The method of claim 9 , wherein the database is a blockchain database.

12 . The method of claim 9 , wherein the PII is obfuscated by replacing identified PII with unique nonces.

13 . The method of claim 12 , wherein the obfuscation dictionary is a nonce-to-original sourceblock dictionary.

14 . The method of claim 10 , wherein the parameters include a range of records to be decoded.

15 . The method of claim 14 , wherein the range of records comprises unique transaction identifiers for each record in the range of records.

16 . The method of claim 9 , wherein the requestor purchases access rights to one or more records of information.

Assignees

• Atombeam Technologies Inc

Inventors

• Cooper Joshua
• Riahi Aliasghar
• Yeomans Charles

Classifications

• H03M7/6005

  Decoder aspects · CPC title

• G06N20/00

  Machine learning · CPC title

• H03M7/4062

  Coding table adaptation · CPC title

• H03M7/6076

  Selection between compressors of the same type · CPC title

• H03M7/3059 Primary

  Digital compression and data reduction techniques where the original information is represented by a subset or similar information, e.g. lossy compression · CPC title