Secure Data Repository with Copy Tracking for Privacy Compliance
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Solution Overview
Problem
Existing data repositories fail to effectively track and delete user data from researcher client computers after it has been altered, leading to potential breaches of user privacy and trust, as the linkage between user data and researchers breaks down, making it difficult to ensure data is completely removed upon user request.
Innovation Solution
A system that utilizes a secure repository to manage user data, associating both original and processed data with users, ensuring deletion only after anonymization through processing, and employing a computational grid for data processing, with metadata tags and secure virtual private networks to maintain data integrity and user privacy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If user data is distributed to researcher client computers for processing, then research productivity and data accessibility are improved, but the ability to track and delete original user data is lost when data is altered
Solution Approach 1:
The system creates copies of user data for researcher processing while maintaining the ability to track these copies through unique identifiers. Researchers work with copied data locally, which improves productivity, while the copy tracking mechanism ensures that deletion requests can still be honored by identifying and removing all copies through their tracked identifiers.
Solution Approach 2:
The data management system is segmented into multiple components: a secure repository for original data, distributed client computers for processing, and a copy tracking system. This segmentation allows each component to perform its specialized function while maintaining overall system coherence through standardized interfaces and tracking mechanisms.
2Adaptability or versatility
If data is processed and altered on client computers, then data utility for research is improved, but the linkage between user data and researchers breaks down
Solution Approach 1:
The system implements feedback mechanisms where processed data is reported back to the secure repository with metadata about the transformations applied. This feedback loop maintains the linkage between original and processed data by recording the data lineage, allowing the system to track how user data has been modified while preserving the ability to manage and delete the data according to user preferences.
3Object-affected harmful factors
If complete data deletion is implemented upon user request, then user privacy protection is improved, but researcher ability to access and use data is compromised
Solution Approach 1:
The system performs preliminary actions by creating and tracking copies of data before deletion is requested. When a user requests deletion, the system can quickly identify all copies through the tracking mechanism and remove them simultaneously, ensuring complete privacy protection without requiring researchers to manually locate and delete each copy, thus maintaining research continuity for other datasets.
Solution Approach 2:
The copy tracking system acts as an intermediary between user privacy requests and researcher data access. It receives deletion requests, identifies all relevant copies through tracking information, and coordinates their removal while notifying researchers, thereby mediating between the conflicting needs of privacy protection and research productivity.
4Reliability
If data is stored in a centralized secure repository, then data security and user privacy are improved, but researcher access and data processing capability are reduced
Solution Approach 1:
The system segments data storage and processing functions: the secure repository stores original data and tracking information, while researcher client computers store and process copies of the data. This segmentation allows the secure repository to maintain high security standards for original data while researchers enjoy the processing efficiency of local copies, resolving the contradiction between security and productivity.
Data Source
AI summary
A secure repository receives and stores user data, and shares the user data with trusted client devices. The user data may be shared individually or as part of bundled data relating to multiple users, but in either case, the secure repository associates specific data with specific users. This association is maintained by the trusted client devices, even after the data is altered by processing on the client device. If a user requests a purge of their data, the system deletes and/or disables that data on both the repository and the client devices, as well as deleting and/or disabling processed data derived from that user's data, unless a determination has been made that the processed data no longer contains confidential information.