Secure Data Linking Across Independent Enterprise Systems
Solution Overview
Problem
Current data matching algorithms in heterogeneous systems often result in false negatives or false positives, leading to incorrect data transactions or duplicate records due to variations in attributes used to describe subjects across different systems and enterprises.
Innovation Solution
A system and method for securely linking and matching data attributes across independent data systems of multiple enterprises by using a private database and a reference database, where query attributes are matched to determine unique associations, and additional attributes are stored or combined to ensure accurate record linking.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional matching algorithms are used to compare attributes between systems, then data transactions can be processed when all attributes match, but false negatives occur causing incorrect rejection of valid transactions or creation of duplicate records
Solution Approach 1:
The patent introduces a reference data system as an intermediary between private data systems. This reference system contains reference data records with reference attributes that serve as a mediator to facilitate accurate matching. The reference data system receives query messages from private data systems, performs matching using reference attributes, and returns results, thereby eliminating false negatives while maintaining reliability of data transactions.
2Productivity
If matching algorithms are used to determine attribute equivalence, then data transactions can proceed when matches are found, but false positives occur causing incorrect acceptance of non-matching records
Solution Approach 1:
The patent segments the matching process into distinct components: private data records with private attributes, reference data records with reference attributes, and query messages that traverse between them. This segmentation allows for controlled matching where query attributes are compared against reference attributes, and only verified matches are accepted, thereby reducing false positives while maintaining productivity.
3Measurement precision
If attributes are shared across enterprises to improve matching accuracy, then record linking becomes more accurate, but privacy of sensitive attributes is compromised
Solution Approach 1:
The reference data system acts as a privacy-preserving intermediary. Private data systems send query attributes to the reference data system without directly sharing their private attributes with other enterprises. The reference data system performs matching using its reference attributes and returns results, enabling accurate matching while preventing direct exposure of sensitive private attributes, thus maintaining privacy security.
4Measurement precision
If a comprehensive reference database is created to store all known attributes, then matching accuracy improves, but system complexity increases
Solution Approach 1:
The reference data system serves multiple functions: it stores reference data records with reference attributes, receives and processes query messages from multiple private data systems, performs matching operations, and returns results. This multi-functionality consolidates what would otherwise require multiple separate matching systems, reducing overall system complexity while maintaining high matching accuracy through comprehensive reference data.
Data Source
AI summary
A methods, systems, and devices for secure linking and matching of data elements across independent data systems of a first and a second enterprise are disclosed. The system includes a first private data system having a first private database that may include all attributes known to the first enterprise A reference data system having a reference database and is also part of the first enterprise. The reference database may include all known attributes regarding data records contained any data system that is in communication with and/or has access to the reference database. A first set of query attributes may be used determine whether a subject represented by the first set of query attributes associates uniquely with a subject of any private data record stored in the first private database. A similar comparison may be made in the reference database.