Selling Privacy in Blockchain Transactions

TL;DR

This paper explores economic mechanisms to improve statistical privacy in blockchain transactions, proposing auction-based and market-based solutions that balance privacy, revenue, and social welfare.

Contribution

It introduces novel auction and market mechanisms that incorporate privacy preferences into blockchain transaction protocols, ensuring incentive compatibility and approximate optimality.

Findings

Optimal sealed-bid auction characterized for privacy-aware transactions.

Comparison of Dutch auction revenue to optimal auction as rounds increase.

A posted-price mechanism guarantees constant approximation of social welfare.

Abstract

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.