Personalized Difficulty Adjustment for Countering the Double-Spending Attack in Proof-of-Work Consensus Protocols

TL;DR

This paper introduces a personalized difficulty adjustment mechanism in proof-of-work systems to reduce double-spending risks by decreasing the likelihood of consecutive block wins, enhancing system trustworthiness.

Contribution

It proposes a novel PDA mechanism that adjusts participant difficulties based on past wins, modeled through a high-order Markov chain for improved security.

Findings

PDA reduces the probability of consecutive winning.

The system can be effectively modeled by a high-order Markov chain.

PDA enhances the trustworthiness of PoW systems.

Abstract

Bitcoin is the first secure decentralized electronic currency system. However, it is known to be inefficient due to its proof-of-work (PoW) consensus algorithm and has the potential hazard of double spending. In this paper, we aim to reduce the probability of double spending by decreasing the probability of consecutive winning. We first formalize a PoW-based decentralized secure network model in order to present a quantitative analysis. Next, to resolve the risk of double spending, we propose the personalized difficulty adjustment (PDA) mechanism which modifies the difficulty of each participant such that those who win more blocks in the past few rounds have a smaller probability to win in the next round. To analyze the performance of the PDA mechanism, we observe that the system can be modeled by a high-order Markov chain. Finally, we show that PDA effectively decreases the probability of consecutive winning and results in a more trustworthy PoW-based system.