Publications by authors named "Phillipp Schoppmann"
Article Synopsis
- Record linkage is vital for connecting datasets containing personally identifiable information (PII) in various fields, especially in healthcare, but privacy laws limit sharing this data.
- The study introduces a privacy-preserving record linkage (PPRL) framework that utilizes secure multi-party computation, enabling linkage without risking PII exposure or requiring a trusted third party.
- Performance benchmarks demonstrate that the proposed solution can efficiently link patient records, achieving notable speed even over slow network connections, and relevant source code is openly accessible on GitHub.
A Secure Multi-Party Computation Protocol for Time-To-Event Analyses.
Stud Health Technol Inform
June 2020
The cryptographic method Secure Multi-Party Computation (SMPC) could facilitate data sharing between health institutions by making it possible to perform analyses on a "virtual data pool", providing an integrated view of data that is actually distributed - without any of the participants having to disclose their private data. One drawback of SMPC is that specific cryptographic protocols have to be developed for every type of analysis that is to be performed. Moreover, these protocols have to be optimized to provide acceptable execution times.
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