Genetic Data De-identification via Segmented Mapping
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Solution Overview
Problem
Current techniques for sharing genetic and personal data are basic, vulnerable to attacks, and do not effectively separate identifying data from personal data, potentially compromising individual privacy.
Innovation Solution
A system that separates identifying data from personal data by using a logically separate database for mapping data, ensuring that unauthorized users cannot associate identifying data with personal data without access to the mapping data, thereby enhancing data security and privacy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If identifying data and personal data are stored together in the same database, then data access and sharing are simplified, but security is compromised because unauthorized users can directly associate identifying data with personal data
Solution Approach 1:
The system divides the database into separate tables: an identifying data table storing personal identifiers (name, address, SSN), a personal data table storing genetic and health information, and a mapping table storing encrypted associations. This segmentation prevents unauthorized users from directly linking identifying data with personal data while maintaining secure access capabilities.
Solution Approach 2:
The patent introduces an intermediary mapping table that contains encrypted foreign keys linking identifying data to personal data. This intermediary layer acts as a security barrier, requiring decryption and authentication to associate identifying information with personal information, thus maintaining security while enabling controlled access.
2Reliability
If identifying data is separated from personal data into different databases, then security is improved by preventing unauthorized association, but system complexity increases due to multiple separate storage systems
Solution Approach 1:
The patent combines multiple separate database components (identifying data table, personal data table, mapping table) into a single integrated database system. This approach maintains the security benefits of separation while reducing system complexity by keeping all components within one database environment, simplifying management and access control.
Solution Approach 2:
The system creates encrypted copies of foreign keys in the mapping table that link identifying data to personal data without exposing the actual association. These encrypted copies maintain the relational integrity needed for data access while preventing unauthorized users from deciphering the links between identifying and personal information.
3Ease of manufacture
If basic data sharing techniques are used, then implementation is simple, but the capability to protect privacy while sharing data is limited
Solution Approach 1:
The patent applies encryption to the foreign keys in the mapping table, changing the parameter state from plaintext to encrypted format. This transformation maintains the functional capability to link data while fundamentally altering the security properties, preventing unauthorized users from reading or associating the data even if they gain database access.
Data Source
AI summary
A system for separating identifying data from personal data is disclosed. The system includes: a first set of stored data comprising a plurality of identifying data structures containing identifying data; a second set of stored data comprising a plurality of personal data structures containing personal data; a set of mapping data comprising a plurality of mappings, wherein each mapping is between an identifying data structure and a personal data structure; and an application configured to receive mapping data associated with a mapping, determine a mapping associated with the mapping data, and obtain a personal data structure based on the mapping. The set of mapping data is logically separate from the first set of stored data, the second set of stored data, and the application.