Smart Contract Data Anonymization Verification
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Solution Overview
Problem
There is a need for an automatic verification mechanism to ensure that data anonymization is correctly performed and compliant with data privacy regulations, as existing methods lack proof of correct anonymization for audits and compliance with regulations.
Innovation Solution
A computer-implemented method and system that reads in data privacy rules, generates test data, checks anonymized data against test data, and outputs metadata to verify the anonymization process, using a distributed database system with smart contracts to automate the verification and maintain compliance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If data anonymization is performed manually or without verification, then data processing speed is maintained, but compliance with data privacy regulations cannot be proven and audit capability is lost
Solution Approach 1:
The system performs preliminary actions by storing original data before anonymization and generating test data in advance. This allows verification to be conducted systematically by comparing anonymized data against the stored original data and test data, ensuring compliance proof is available before actual data processing occurs.
Solution Approach 2:
The system creates copies of original data for verification purposes. Test data is generated as a copy based on original data characteristics, and anonymized data is compared against these copies. This copying approach enables audit capability without requiring access to sensitive original data during the verification process.
2Reliability
If automated verification mechanisms are implemented, then compliance with data privacy regulations is proven, but system complexity and implementation overhead increase
Solution Approach 1:
The verification system performs self-service by automatically comparing anonymized data against stored original data and test data without requiring external auditors or manual verification processes. The system generates its own verification evidence and maintains compliance proof autonomously, reducing the need for complex external verification infrastructure.
Solution Approach 2:
The system implements feedback mechanisms where anonymized data is continuously verified against original data and test data. The verification results provide feedback on compliance status, allowing the system to automatically adjust and maintain compliance without increasing overall system complexity.
3Extent of automation
If manual data anonymization review is performed, then some level of compliance checking is possible, but automation and consistent audit capability are lacking
Solution Approach 1:
The verification process is segmented into distinct automated components: original data storage, test data generation, anonymized data comparison, and compliance proof generation. Each segment handles a specific verification task, enabling full automation while keeping individual components simple and manageable.
Solution Approach 2:
The system replaces manual mechanical review processes with automated computational verification. Instead of human reviewers manually checking anonymization compliance, the system uses automated data comparison algorithms and computational methods to verify compliance consistently and auditably.
Data Source
AI summary
Provided is a computer-implemented method and system for checking anonymisation of data. Anonymized data are analysed by means of a smart contract process based on data privacy rules automatically raising a flag in case of an anomaly. The smart contract is governed in a decentralized manner where anodes of distributed database can verify the rules specified in the smart contract and/or assess an anomalous situation. To this end, test data are generated at the data source by applying the data privacy rules to the original data. The test data are checked against the anonymized data and depending on the check result metadata are generated. The metadata are provided to nodes of a distributed database for further verification.