The integration of permissioned blockchain such as Hyperledger fabric (HF) and Industrial internet of Things (IIoT) has opened new opportunities for interdependent supply chain partners to improve their performance through data sharing and coordination. The multichannel mechanism, private data collection and querying mechanism of HF enable private data sharing, transparency, traceability, and verification across the supply chain. However, the existing querying mechanism of HF needs further improvement for statistical data sharing because the query is evaluated on the original data recorded on the ledger. As a result, it gives rise to privacy issues such as leak of business secrets, tracking of resources and assets, and disclose of personal information. Therefore, we solve this problem by proposing a differentially private enhanced permissioned blockchain for private data sharing in the context of supply chain in IIoT which is known as (EDH-IIoT). We propose algorithms to efficiently utilize the $\epsilon$ through the reuse of the privacy budget for the repeated queries. Furthermore, the reuse and tracking of $\epsilon$ enable the data owner to get ensure that $\epsilon$ does not exceed the threshold which is the maximum privacy budget ($\epsilon_{t}$). Finally, we model two privacy attacks namely linking attack and composition attack to evaluate and compare privacy preservation, and the efficiency of reuse of {\epsilon} with the default chaincode of HF and traditional differential privacy model, respectively. The results confirm that EDH-IIoT obtains an accuracy of 97% in the shared data for $\epsilon_{t}$ = 1, and a reduction of 35.96% in spending of $\epsilon$.

翻译：将Hyperledger Fabric（HF）等许可区块链与工业物联网（IIoT）相融合，为相互依赖的供应链合作伙伴通过数据共享与协同提升绩效开辟了新机遇。HF的多通道机制、私有数据收集与查询机制实现了跨供应链的私有数据共享、透明度、可追溯性与验证。然而，HF现有的查询机制在统计数据共享方面仍需改进，因为查询是基于账本记录的原始数据执行的。由此引发业务秘密泄露、资源与资产追踪以及个人信息披露等隐私问题。为此，我们提出一种面向工业物联网供应链场景的差分隐私增强型许可区块链（EDH-IIoT），通过复用隐私预算以高效利用ε来解决重复查询问题。此外，ε的复用与追踪使数据所有者能够确保ε不超过最大隐私预算阈值（ε_t）。最后，我们分别构建了链接攻击与组合攻击两种隐私攻击模型，评估了EDH-IIoT的隐私保护能力及ε复用效率，并与HF默认链码及传统差分隐私模型进行对比。结果表明，当ε_t=1时，EDH-IIoT在共享数据上的准确率达到97%，且ε消耗减少35.96%。