Homomorphic Encryption for Privacy-Preserving Blockchain Data Analysis

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Solution Overview

Problem

Blockchain networks face challenges in performing data analysis on privacy-protected data without risking data leakage, as decryption is often required for analysis, potentially violating privacy laws and increasing data transmission complexity.

Innovation Solution

A computing method that homomorphically encrypts data before analysis, allowing encrypted data to be processed on a blockchain network without decryption, ensuring privacy preservation through homomorphic encryption engines and secure data paths within the blockchain.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Productivity

If data is decrypted for analysis on blockchain network, then data analysis can be performed, but data leakage risk increases and privacy protection is compromised

Engineering Contradiction:
Improvedata analysis capabilityVSAvoiddata leakage risk
Core Design Contradiction:
ProductivityVSObject-affected harmful factors

Solution Approach 1:

Homomorphic encryption serves as an intermediary mechanism that enables data analysis on the blockchain network without requiring decryption. The encryption scheme allows computational operations to be performed on encrypted data, producing encrypted results that can be decrypted only by authorized parties, thus eliminating data leakage risk while maintaining analysis capability

Inventive Principle:
Principle #24Intermediary (Mediator)

Solution Approach 2:

The patent changes the state parameter of data from plaintext to homomorphically encrypted form. This parameter change allows the data to maintain its analytical utility while being protected from unauthorized access. The encrypted data can undergo computational transformations without being decrypted, preserving privacy throughout the analysis process

Inventive Principle:
Principle #35Parameter changes

2Object-affected harmful factors

If data is transmitted in encrypted state, then privacy protection is maintained, but data transmission and processing complexity increases

Engineering Contradiction:
Improveprivacy protectionVSAvoidencryption processing complexity
Core Design Contradiction:
Object-affected harmful factorsVSDevice complexity

Solution Approach 1:

The patent extracts the decryption operation from the blockchain network processing flow and concentrates it in authorized client devices. This extraction allows the blockchain network to handle only encrypted data using simplified validation logic, while complex decryption operations are performed only when absolutely necessary and authorized, reducing overall system complexity

Inventive Principle:
Principle #2Taking out (Extraction)

Solution Approach 2:

Data is encrypted using homomorphic encryption schemes before being uploaded to the blockchain network. This preliminary encryption action ensures that privacy protection is built into the system architecture from the outset, eliminating the need for complex runtime privacy management and reducing processing complexity during blockchain operations

Inventive Principle:
Principle #10Preliminary action

3Productivity

If medical data is transmitted to external systems for analysis, then data analysis capability is improved, but violation of medical law may occur

Engineering Contradiction:
Improvemedical data analysis capabilityVSAvoidlegal compliance
Core Design Contradiction:
ProductivityVSReliability

Solution Approach 1:

Homomorphic encryption acts as a legal and technical intermediary that enables medical data to be shared with external blockchain-based analysis systems while maintaining compliance with medical privacy laws. The encryption ensures that data remains protected during transmission and processing, allowing analysis capability improvement without violating legal requirements for medical data protection

Inventive Principle:
Principle #24Intermediary (Mediator)

Data Source

PatentUS11936792B2Method and system for providing privacy-preserving data analysis
Publication Date: 2024.03.19 COMMON COMP INC
  • US11936792B2 patent drawing
  • US11936792B2 patent drawing
  • US11936792B2 patent drawing

AI summary

A computing method for privacy-preserving data analysis is provided, in which the computing method is performed by at least one processor and includes receiving a data analysis request including data-to-be-analyzed from a client, homomorphically encrypting the data-to-be-analyzed using an encryption engine, and uploading the homomorphically encrypted data-to-be-analyzed to a target path of a blockchain, and then, the method includes, based on the request to check analysis result, decrypting an analysis result of the homomorphically encrypted data stored in a designated path of the blockchain by using the encryption engine, and providing the decrypted analysis result to the client, in which the analysis result of the homomorphically encrypted data is data analyzed by a worker linked to the blockchain, and stored in a designated path in association with the target path of the blockchain.