A sandbox study proposal for private and distributed health data analysis

Fuente: arXiv
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Main Authors: Brännvall, Rickard, Svensson, Hanna, Kaliyaperumal, Kannaki, Burden, Håkan, Stenberg, Susanne
Format: Preprint
Published: 2025
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author Brännvall, Rickard
Svensson, Hanna
Kaliyaperumal, Kannaki
Burden, Håkan
Stenberg, Susanne
author_facet Brännvall, Rickard
Svensson, Hanna
Kaliyaperumal, Kannaki
Burden, Håkan
Stenberg, Susanne
contents This paper presents a sandbox study proposal focused on the distributed processing of personal health data within the Vinnova-funded SARDIN project. The project aims to develop the Health Data Bank (Hälsodatabanken in Swedish), a secure platform for research and innovation that complies with the European Health Data Space (EHDS) legislation. By minimizing the sharing and storage of personal data, the platform sends analysis tasks directly to the original data locations, avoiding centralization. This approach raises questions about data controller responsibilities in distributed environments and the anonymization status of aggregated statistical results. The study explores federated analysis, secure multi-party aggregation, and differential privacy techniques, informed by real-world examples from clinical research on Parkinson's disease, stroke rehabilitation, and wound analysis. To validate the proposed study, numerical experiments were conducted using four open-source datasets to assess the feasibility and effectiveness of the proposed methods. The results support the methods for the proposed sandbox study by demonstrating that differential privacy in combination with secure aggregation techniques significantly improves the privacy-utility trade-off.
format Preprint
id arxiv_https___arxiv_org_abs_2501_14556
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle A sandbox study proposal for private and distributed health data analysis
Brännvall, Rickard
Svensson, Hanna
Kaliyaperumal, Kannaki
Burden, Håkan
Stenberg, Susanne
Cryptography and Security
Computers and Society
Distributed, Parallel, and Cluster Computing
68M14 (Primary) 92C60, 68P25, 68P20 (Secondary)
K.4.1; J.3.2; H.2.8; D.4.6
This paper presents a sandbox study proposal focused on the distributed processing of personal health data within the Vinnova-funded SARDIN project. The project aims to develop the Health Data Bank (Hälsodatabanken in Swedish), a secure platform for research and innovation that complies with the European Health Data Space (EHDS) legislation. By minimizing the sharing and storage of personal data, the platform sends analysis tasks directly to the original data locations, avoiding centralization. This approach raises questions about data controller responsibilities in distributed environments and the anonymization status of aggregated statistical results. The study explores federated analysis, secure multi-party aggregation, and differential privacy techniques, informed by real-world examples from clinical research on Parkinson's disease, stroke rehabilitation, and wound analysis. To validate the proposed study, numerical experiments were conducted using four open-source datasets to assess the feasibility and effectiveness of the proposed methods. The results support the methods for the proposed sandbox study by demonstrating that differential privacy in combination with secure aggregation techniques significantly improves the privacy-utility trade-off.
title A sandbox study proposal for private and distributed health data analysis
topic Cryptography and Security
Computers and Society
Distributed, Parallel, and Cluster Computing
68M14 (Primary) 92C60, 68P25, 68P20 (Secondary)
K.4.1; J.3.2; H.2.8; D.4.6
url https://arxiv.org/abs/2501.14556