We study methods to enhance statistical privacy in blockchain transactions. We analyze economic mechanisms for privacy-aware transaction owners whose utility depends not only on the outcome of the mechanism but also negatively on the exposure of their economic preferences. First, we consider an order flow auction, where a user auctions off to specialized agents, called searchers, the right to execute her transaction while maintaining a degree of privacy. We examine how the degree of privacy affects the revenue of the auction and, broadly, the net utility of the privacy-aware user. In this new setting, we characterize the optimal auction, which is a sealed-bid auction. Subsequently, we analyze a variant of a Dutch auction in which the user gradually decreases the price and the degree of privacy until the transaction is sold. We compare the revenue of this auction to that of the optimal one as a function of the number of communication rounds. Then, we introduce a two-sided market - a privacy marketplace - with multiple users selling their transactions under their privacy preferences to multiple searchers. We propose a posted-price mechanism for the two-sided market that guarantees constant approximation of the optimal social welfare while maintaining incentive compatibility (from both sides of the market) and budget balance. This work builds on the emerging literature on privacy-preserving mechanism design, integrating statistical privacy guarantees into economic protocols to capture the impact of information leakage on blockchain users' utility.

翻译：本研究探讨增强区块链交易统计隐私的方法。我们分析具有隐私意识的交易所有者的经济机制，其效用不仅取决于机制结果，还与其经济偏好的暴露程度呈负相关。首先，我们考虑订单流拍卖机制，用户通过向专业代理（称为搜索者）拍卖交易执行权，同时保持一定程度的隐私。我们研究隐私程度如何影响拍卖收益，以及更广泛地影响隐私意识用户的净效用。在此新设定下，我们刻画了最优拍卖机制——密封投标拍卖。随后，我们分析荷兰式拍卖的变体，其中用户逐步降低价格和隐私程度直至交易完成。通过比较不同通信轮数下该拍卖与最优拍卖的收益差异，我们发现...（原文此处为隐含结论）。接着，我们构建双边市场——隐私交易市场——允许多用户在满足其隐私偏好的条件下向多搜索者出售交易。我们提出一种保证最优社会福利常数近似比的定价机制，同时保持激励兼容性（市场双边）与预算平衡。本研究基于新兴的隐私保护机制设计文献，将统计隐私保障融入经济协议，以量化信息泄露对区块链用户效用的影响。