In blockchain systems, fair transaction ordering is crucial for a trusted and regulation-compliant economic ecosystem. Unlike traditional State Machine Replication (SMR) systems, which focus solely on liveness and safety, blockchain systems also require a fairness property. This paper examines these properties and aims to eliminate algorithmic bias in transaction ordering services. We build on the notion of equal opportunity. We characterize transactions in terms of relevant and irrelevant features, requiring that the order be determined solely by the relevant ones. Specifically, transactions with identical relevant features should have an equal chance of being ordered before one another. We extend this framework to define a property where the greater the distance in relevant features between transactions, the higher the probability of prioritizing one over the other. We reveal a surprising link between equal opportunity in SMR and Differential Privacy (DP), showing that any DP mechanism can be used to ensure fairness in SMR. This connection not only enhances our understanding of the interplay between privacy and fairness in distributed computing but also opens up new opportunities for designing fair distributed protocols using well-established DP techniques.

翻译：在区块链系统中，公平的交易排序对于构建可信且合规的经济生态系统至关重要。与仅关注活性与安全性的传统状态机复制系统不同，区块链系统还需满足公平性要求。本文审视这些特性，旨在消除交易排序服务中的算法偏见。我们基于机会平等的概念展开研究，将交易区分为相关特征与无关特征，要求排序结果仅由相关特征决定。具体而言，具有相同相关特征的交易应拥有相等的排序优先概率。我们扩展该框架以定义如下特性：交易间相关特征差异越大，则一方优先于另一方的概率越高。我们揭示了状态机复制中的机会平等与差分隐私之间令人惊异的联系，证明任何差分隐私机制都可用于保障状态机复制的公平性。这一关联不仅深化了我们对分布式计算中隐私与公平相互作用的理解，更为利用成熟的差分隐私技术设计公平的分布式协议开辟了新途径。