Blockchain-Based Sensitive Data Tracking in Custom Integration
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Solution Overview
Problem
Current data integration processes lack efficient methods to identify and track sensitive personal information, particularly in customized data integration scenarios, which poses challenges for compliance with regulations like the GDPR and increases the risk of data infringement.
Innovation Solution
A blockchain-based data protection system is implemented to track the physical storage locations of sensitive personal information throughout customized data integration processes, using a graphical user interface to model data flows and generate metadata tracking blocks, ensuring immutable records of data manipulation and storage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional data integration processes are used, then data processing flexibility is maintained, but the ability to identify and track sensitive personal information deteriorates
Solution Approach 1:
The patent introduces blockchain technology as an intermediary layer between data integration processes and sensitive information tracking. The blockchain ledger serves as a mediator that automatically records and tracks personal information without requiring complex modifications to existing data integration systems, thereby improving tracking precision while maintaining acceptable system complexity
Solution Approach 2:
The patent creates a parallel tracking system that copies metadata about data flows into a blockchain ledger. This copying mechanism allows the original data integration processes to continue unchanged while a separate, immutable record of sensitive information handling is maintained, resolving the contradiction between tracking precision and system complexity
2Reliability
If detailed tracking of personal information is implemented, then GDPR compliance capability is improved, but the time and resources required for data management increase
Solution Approach 1:
The patent implements preliminary action by automatically recording data flow metadata in the blockchain ledger as data moves through integration processes. This real-time, automated tracking eliminates the need for manual compliance auditing later, thereby improving GDPR compliance reliability while reducing the time and resources required for data management
Solution Approach 2:
The blockchain ledger provides continuous feedback about the location and handling of personal information throughout the data integration process. This automated feedback mechanism enables real-time compliance monitoring without requiring additional manual intervention, resolving the contradiction between compliance reliability and time consumption
3Reliability
If blockchain tracking is implemented, then data security and immutability are improved, but the computational overhead and processing speed deteriorate
Solution Approach 1:
The patent extracts only the essential metadata related to personal information handling from the main data flow and stores it in the blockchain ledger. By separating the tracking function from the primary data processing, the system achieves improved data security through blockchain immutability while minimizing the computational overhead and maintaining data processing speed
Data Source
AI summary
A method of block chain based data protection may comprise receiving a user block chain instruction to record a address-identified memory location at which a dataset field value containing sensitive personal information is stored pursuant to a customized data integration process modeled via a graphical user interface, creating a block chain associated with the dataset field value, receiving an identification of the address-identified memory location from a customized data integration process remote execution location, and creating a first block storing the identification of the address-identified memory location within the block chain. The method may further comprise receiving a user deletion instruction to delete the dataset field value from the address-identified memory location, automatically generating a runtime engine and machine executable deletion code instructions for deletion of the dataset field value from the address-identified memory location, and transmitting the runtime engine and the machine executable deletion code instructions for execution at the remote execution location.