评估与守护群体智慧：面向众包真值推理的零知识证明
Evaluate and Guard the Wisdom of Crowds: Zero Knowledge Proofs for Crowdsourcing Truth Inference
AI总结：
针对众包场景中聚合器可信度与贡献者输入公平评估难题，提出融合零知识证明与真值推理算法的zkTI协议，实现可验证的诚实聚合与公平评估，经实验验证高效鲁棒，适用于众包与云计算场景。
摘要：
众包已成为缓解外包云计算中正确性与安全风险的主流方法。该过程由聚合器分发任务、收集响应并聚合来自多个数据源的结果，借助群体智慧完成复杂任务，在提升任务完成准确率的同时，降低单一实体恶意行为带来的风险。但一个关键问题随之而来：如何确保聚合器诚实地履行职责，且每位贡献者的输入都得到公平评估？针对这一挑战，我们提出了名为$\boldsymbol{\textsf{zkTI}}$的新型协议。该方案既能保证聚合器诚实执行聚合过程，又能实现对各数据源的公平评估，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理算法相结合。在该协议下，聚合过程兼具正确性与可验证性，同时能确保对数据源可靠性的公平评估。实验结果表明，该协议具备高效性与鲁棒性，是众包与云计算领域可行且有效的解决方案。
英文摘要：
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.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
