From Isolation to Integration: A Reputation-Backed Auditable Model for Cohort Data Sharing

Abstract:

Data sharing is vital to breaking data silos and maximizing information value. However, practical implementations often rely on cloud servers, raising trust concerns that prevent Data Centers (DCs) from sharing sensitive data. Motivated by the need to ensure both the quality and quantity of shared data, we proposed a reputation-driven, auditable data-sharing model that uses blockchain to enable secure, distributed sharing. Our model faces two primary challenges: (1) ensuring data quality in distributed settings, where existing cloud-based audit schemes requiring high computational resources are unsuitable, and (2) promoting active sharing of scarce data, where current incentive mechanisms fail to encourage proactive participation. To address these, we introduce the Secure Auditable Sharing Protocol (SASP) and the fair Reputation-driven Proactive Sharing Mechanism (RPSM). SASP enhances ElGamal encryption and integrates efficient hashing techniques for privacy-preserving audits of ciphertext integrity and deduplication without relying on costly bilinear mappings. RPSM tackles the challenge of selfish DCs by incorporating a committee mechanism and consensus algorithm, ensuring fair incentives to encourage active participation. Our implementation and real-world case study demonstrate that the proposed model effectively guarantees the quality and quantity of shared data, offering a novel solution to the data silo problem in distributed architectures.

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