# US 12,216,626 B2 · Secure zero knowledge data transformation and validation > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 12,216,626 B2 - Document ID: US12216626B2 - Status: Granted - Kind: B2 - Application number: 18/109,906 - Filed: 2023-02-15 - Published: 2024-01-25 - Granted: 2025-02-04 - Earliest claimed: 2020-01-21 - Assignees: LO3 Energy Inc. - Applicants: LO3 Energy Inc. - Inventors: Lawrence Orsini - Web page: https://patentgrep.com/patent/US12216626B2 ## CPC - G06F 16/215: Improving data quality; Data cleansing, e.g. de-duplication, removing invalid entries or correcting typographical errors - G06F 40/20: Natural language analysis (semantic analysis of natural language G06F40/30) - G06F 16/152: {using file content signatures, e.g. hash values} - G06F 16/258: {Data format conversion from or to a database} - G06F 40/00: Handling natural language data (speech analysis or synthesis, speech recognition G10L) - G06N 5/022: Knowledge engineering; Knowledge acquisition - G06N 20/00: Machine learning - H04L 9/3218: {using proof of knowledge, e.g. Fiat-Shamir, GQ, Schnorr, ornon-interactive zero-knowledge proofs} - H04L 9/3247: {involving digital signatures} - H04L 9/3271: {using challenge-response} - G06N 7/01: Probabilistic graphical models, e.g. probabilistic networks - G06F: ELECTRIC DIGITAL DATA PROCESSING (computer systems based on specific computational models G06N) - G06N: COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS - H04L: TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION (arrangements common to telegraphic and telephonic communication H04M) ## Abstract This specification allows for secure, original data to be attributed, transformed attestably and managed within a data center or distributed across a peer to peer network using zero knowledge proofs that allow the holder of transformed data to verify, with certainty, that their transformed data was derived from the attributed data source, without visibility into the contents of that source data. ## Claims ### Claim 1 A computing device implemented method comprising: receiving cryptographically secured data representing a request for information stored at a node of a distributed network based on whether the cryptographically secured data has been previously validated, the stored information containing sensitive information; semantically searching, using a machine learning system trained on historical data, the received cryptographically secured data to identify one or more data types reflected in the received cryptographically secured data; selecting one or more digitally signed and authenticated transforms based on the one or more data types of the received cryptographically secured data and data types used by the one or more digitally signed and authenticated transforms; evaluating the received cryptographically secured data using the one or more selected digitally signed and authenticated transforms to generate an evaluated cryptographically secured result that does not contain sensitive information; and providing the evaluated cryptographically secured result to the distributed network in response to the request for information. ### Claim 2 (depends on 1) The computing device implemented method of claim 1, wherein the received cryptographically secured data comprises a data transformation request comprising an address of the received cryptographically secured data. ### Claim 3 (depends on 1) The computing device implemented method of claim 1, wherein evaluating the received cryptographically secured data using the one or more selected digitally signed and authenticated transforms comprises encoding an address of the received cryptographically secured data into the evaluated cryptographically secured result and encoding an address of the one or more selected digitally signed and authenticated transforms into the evaluated cryptographically secured result. ### Claim 4 (depends on 1) The computing device implemented method of claim 1, wherein selecting the one or more digitally signed and authenticated transforms comprises comparing a signature representing a jurisdiction of a particular transform with a jurisdiction of the node, wherein selecting the one or more digitally signed and authenticated transforms is further based on the comparison. ### Claim 5 (depends on 1) The computing device implemented method of claim 1, wherein semantically searching the received cryptographically secured data comprises determining one or more sequences of data fields embedded in the received cryptographically secured data using the machine learning system trained using the historical data. ### Claim 6 (depends on 1) The computing device implemented method of claim 1, wherein the sensitive information comprises personally identifiable information. ### Claim 7 A system comprising: a computing device comprising: a memory configured to store instructions; and a processor to execute the instructions to perform operations comprising: receiving cryptographically secured data representing a request for information stored at a node of a distributed network based on whether the cryptographically secured data has been previously validated, the stored information containing sensitive information; semantically searching, using a machine learning system trained on historical data, the received cryptographically secured data to identify one or more data types reflected in the received cryptographically secured data; selecting one or more digitally signed and authenticated transforms based on the one or more data types of the received cryptographically secured data and data types used by the one or more digitally signed and authenticated transforms; evaluating the received cryptographically secured data using the one or more selected digitally signed and authenticated transforms to generate an evaluated cryptographically secured result that does not contain sensitive information; and providing the evaluated cryptographically secured result to the distributed network in response to the request for information. ### Claim 8 (depends on 7) The system of claim 7, wherein the received cryptographically secured data comprises a data transformation request comprising an address of the received cryptographically secured data. ### Claim 9 (depends on 7) The system of claim 7, wherein evaluating the received cryptographically secured data using the one or more selected digitally signed and authenticated transforms comprises encoding an address of the received cryptographically secured data into the evaluated cryptographically secured result and encoding an address of the one or more selected digitally signed and authenticated transforms into the evaluated cryptographically secured result. ### Claim 10 (depends on 7) The system of claim 7, wherein selecting the one or more digitally signed and authenticated transforms comprises comparing a signature representing a jurisdiction of a particular transform with a jurisdiction of the node, wherein selecting the one or more digitally signed and authenticated transforms is further based on the comparison. ### Claim 11 (depends on 7) The system of claim 7, wherein semantically searching the received cryptographically secured data comprises determining one or more sequences of data fields embedded in the received cryptographically secured data using the machine learning system trained using the historical data. ### Claim 12 (depends on 7) The system of claim 7, wherein the sensitive information comprises personally identifiable information. ### Claim 13 One or more non-transitory computer readable media storing instructions that are executable by a processing device, and upon such execution cause the processing device to perform operations comprising: receiving cryptographically secured data representing a request for information stored at a node of a distributed network based on whether the cryptographically secured data has been previously validated, the stored information containing sensitive information; semantically searching, using a machine learning system trained on historical data, the received cryptographically secured data to identify one or more data types reflected in the received cryptographically secured data; selecting one or more digitally signed and authenticated transforms based on the one or more data types of the received cryptographically secured data and data types used by the one or more digitally signed and authenticated transforms; evaluating the received cryptographically secured data using the one or more selected digitally signed and authenticated selected transforms to generate an evaluated cryptographically secured result that does not contain sensitive information; and providing the evaluated cryptographically secured result to the distributed network in response to the request for information. ### Claim 14 (depends on 13) The one or more non-transitory computer readable media of claim 13, wherein the received cryptographically secured data comprises a data transformation request comprising an address of the received data. ### Claim 15 (depends on 13) The one or more non-transitory computer readable media of claim 13, wherein evaluating the received cryptographically secured data using the one or more selected digitally signed and authenticated transforms comprises encoding an address of the received cryptographically secured data into the evaluated cryptographically secured result and encoding an address of the one or more selected digitally signed and authenticated transforms into the evaluated cryptographically secured result. ### Claim 16 (depends on 13) The system one or more non-transitory computer readable media of claim 13, wherein selecting the one or more digitally signed and authenticated transforms comprises comparing a signature representing a jurisdiction of a particular transform with a jurisdiction of the node, wherein selecting the one or more digitally signed and authenticated transforms is further based on the comparison. ### Claim 17 (depends on 13) The one or more non-transitory computer readable media of claim 13, wherein semantically searching the received cryptographically secured data comprises determining one or more sequences of data fields embedded in the received cryptographically secured data using the machine learning system trained using the historical data.