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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.
Abstract:
The TrustNShare project aims to facilitate health data exchange by creating a framework that balances privacy, reputation, and incentives. The approach allows for flexible privacy levels while mitigating the risks of data re-identification, supported by blockchain-based tamper-proof logging. Through a participatory development process involving stakeholders, a reputation model and incentives were established. The data trust enhances data sharing negotiations by informing participants of key factors like user reputation and privacy risks.
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