Temporary Vault for Secure Data Analysis
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Solution Overview
Problem
Current data sharing technologies face challenges in accurately sharing data across different formats and entities due to format incompatibilities and stringent privacy regulations, such as HIPAA and GDPR, which restrict the sharing of personal information, and lack transparency in data processing and analysis.
Innovation Solution
A data communication network architecture that utilizes secure data silos and temporary vaults to anonymize and normalize data, allowing controlled access and processing of shareable data while maintaining privacy, enabling data consumers to analyze a broad spectrum of data without accessing non-shareable information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If data is shared across entities, then data analysis capabilities are enhanced, but data privacy and security are compromised
Solution Approach 1:
A temporary vault acts as an intermediary between data sources and data consumers. The vault receives data from multiple entities, processes it through anonymization and normalization, and makes it available for querying without exposing the original data sources. This mediator approach enables data analysis while preserving privacy by decoupling the data consumer from the data source.
Solution Approach 2:
Instead of sharing original sensitive data, the system creates anonymized copies of the data in the temporary vault. These copies contain the necessary information for analysis but have had personally identifiable information removed or obscured. The copies can be freely queried without compromising the security of the original data sources.
2Adaptability or versatility
If data from multiple entities is combined, then broader data spectrum is available for analysis, but format incompatibilities and processing complexity increase
Solution Approach 1:
The temporary vault performs preliminary processing of data from multiple entities before it becomes available for querying. Data is pre-anonymized, pre-normalized, and pre-integrated into a unified structure. This preliminary action eliminates the need for complex real-time processing when queries are executed, reducing processing complexity while maintaining broad data spectrum availability.
Solution Approach 2:
The system applies parameter changes to data from different entities by standardizing data formats, data types, and structures. Through normalization processes, diverse data formats are transformed into a common schema, enabling seamless integration and querying across multiple data sources without requiring complex format conversion logic at query time.
3Reliability
If anonymization and normalization processes are applied, then data privacy is maintained, but data processing time and computational resources increase
Solution Approach 1:
Anonymization and normalization are performed in advance when data is loaded into the temporary vault, rather than being applied at query time. This preliminary processing ensures privacy compliance is established upfront, and the same processed data can be reused for multiple queries without repeating the computationally intensive anonymization steps, thereby reducing processing time for subsequent operations.
Data Source
AI summary
A method includes obtaining, by a consumer computing device of a data communication network, a temporary credential in accordance with a temporary credential protocol. The method continues with accessing, by the consumer computing device, a temporary vault in accordance with the temporary credential, where the temporary vault stores or is to store a set of shareable data records. The method continues with facilitating, by the consumer computing device, execution of a data analysis function on the set of shareable data records to produce an analytical result. The method continues with receiving, by the consumer computing device from the temporary vault, the analytical result. The method continues with storing, by the consumer computing device, the analytical result in memory associated with the user computing device.