Secure data collaboration among mutually distrustful organizations requires more than encrypted storage: it also needs accountable ownership control, auditable access governance, privacy-preserving transaction execution, and reliable settlement when data are exchanged as digital assets. This paper proposes TrustTrade, a unified multi-party secure data management and transaction framework designed for cross-organization data sharing, trading, and compliance-sensitive analytics. TrustTrade integrates policy-bound data capsules, a tamper-evident provenance ledger, adaptive threshold escrow, verifiable data-payment settlement, and selective audit with revocation rebinding. On four real-dataset-derived workloads, TrustTrade reaches a 90.4–94.8% settlement rate, with a 92.5% average that is 6.4 percentage points higher than the strongest baseline average. Under adversarial request injection, TrustTrade reduces unauthorized release to 0.31% and atomicity violation to 0.38%, corresponding to 93.6% and 93.0% reductions compared with Plain-Market, respectively; compared with Fixed-Escrow, unauthorized release is reduced by 77.4%. TrustTrade also achieves 96.7% dispute-resolution accuracy while maintaining practical settlement latency. These results indicate that jointly designing secure data management and secure data transaction protocols offers a practical path toward trustworthy multi-party data ecosystems.
Chen et al. (Mon,) studied this question.