Crowdsourcing has emerged as a prevalent method for mitigating the risks of correctness and security in outsourced cloud computing. This process involves an aggregator distributing tasks, collecting responses, and aggregating outcomes from multiple data sources. Such an approach harnesses the wisdom of crowds to accomplish complex tasks, enhancing the accuracy of task completion while diminishing the risks associated with the malicious actions of any single entity. However, a critical question arises: How can we ensure that the aggregator performs its role honestly and each contributor's input is fairly evaluated? In response to this challenge, we introduce a novel protocol termed $\mathsf{zkTI}. This scheme guarantees both the honest execution of the aggregation process by the aggregator and the fair evaluation of each data source. It innovatively integrates a cryptographic construct known as zero-knowledge proof with a category of truth inference algorithms for the first time. Under this protocol, the aggregation operates with both correctness and verifiability, while ensuring fair assessment of data source reliability. Experimental results demonstrate the protocol's efficiency and robustness, making it a viable and effective solution in crowdsourcing and cloud computing.

翻译：众包已成为缓解外包云计算中正确性与安全风险的一种普遍方法。该过程涉及聚合器分配任务、收集响应并整合来自多个数据源的输出，通过利用群体智慧完成复杂任务，在提升任务完成精度的同时降低单一实体恶意行为带来的风险。然而，一个关键问题随之产生：如何确保聚合器诚实地履行其职责，且每个贡献者的输入都能得到公平评估？针对这一挑战，我们提出了一种名为$\mathsf{zkTI}$的新型协议。该方案既保证了聚合器对聚合过程的诚实执行，又确保了各数据源的公平评估。它首次创新性地将零知识证明这一密码学构造与一类真值推断算法相结合。在此协议下，聚合操作兼具正确性与可验证性，同时保障对数据源可靠性的公正评估。实验结果表明该协议具有高效性与鲁棒性，使其成为众包与云计算领域中可行且有效的解决方案。