Blockchain Privacy Through Merge Avoidance and Mixing Services: a Hardness and an Impossibility Result

TL;DR

This paper investigates the fundamental computational and theoretical limits of privacy-enhancing strategies in blockchain cryptocurrencies, focusing on merge avoidance and mixing services, revealing NP-hardness and impossibility results.

Contribution

It establishes the NP-hardness of optimal merge avoidance and proves certain impossibility results for incentive-compatible mixing services, advancing understanding of privacy limits in blockchain.

Findings

Optimal merge avoidance is NP-hard

Incentive-compatible mixing services face fundamental impossibility results

Contributes to understanding privacy mechanism limits in blockchain

Abstract

Cryptocurrencies typically aim at preserving the privacy of their users. Different cryptocurrencies preserve privacy at various levels, some of them requiring users to rely on strategies to raise the privacy level to their needs. Among those strategies, we focus on two of them: merge avoidance and mixing services. Such strategies may be adopted on top of virtually any blockchain-based cryptocurrency. In this paper, we show that whereas optimal merge avoidance leads to an NP-hard optimization problem, incentive-compatible mixing services are subject to a certain class of impossibility results. Together, our results contribute to the body of work on fundamental limits of privacy mechanisms in blockchain-based cryptocurrencies.