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TrustNShare - Data Trust Model Balancing Privacy Risk, Reputation, and Incentives.

Cord Spreckelsen¹, Tim Schneider¹, Sven Festag¹

¹Institute of Medical Statistics, Computer and Data Sciences (IMSID), Jena University Hospital, Jena, Germany.

Studies in Health Technology and Informatics

|May 17, 2025

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The TrustNShare project developed a framework for secure health data exchange, balancing privacy and incentives using blockchain technology. This system enhances data sharing negotiations by considering user reputation and privacy risks.

Area of Science:

Health Informatics
Data Security
Blockchain Technology

Background:

Facilitating secure health data exchange is crucial for research and personalized medicine.
Existing frameworks often struggle to balance data utility with robust privacy protection.
Re-identification risks and lack of trust hinder effective health data sharing.

Purpose of the Study:

To develop a novel framework, TrustNShare, for secure and privacy-preserving health data exchange.
To integrate flexible privacy controls, reputation mechanisms, and incentive models.
To mitigate data re-identification risks through blockchain-based logging.

Main Methods:

Participatory development involving diverse stakeholders.
Implementation of a blockchain-based system for tamper-proof logging.

Keywords:

Data trust model blockchain participation privacy re-identification

Related Experiment Videos

Development of a reputation model and incentive structures for data sharing.

Creation of a data trust to inform negotiation processes.

Main Results:

A functional framework enabling flexible privacy levels in health data exchange.
Established reputation and incentive models validated through stakeholder engagement.
Demonstrated mitigation of re-identification risks via secure logging.
Enhanced data sharing negotiations informed by reputation and privacy risk data.

Conclusions:

The TrustNShare framework effectively balances privacy, reputation, and incentives for health data exchange.
Blockchain technology provides a secure and transparent foundation for health data management.
Stakeholder involvement is key to developing trusted and usable data-sharing systems.