A New Outlook on the Profitability of Rogue Mining Strategies in the Bitcoin Network

TL;DR

This paper models the dynamic behavior of rogue mining strategies in Bitcoin by treating the key parameter gamma as a stochastic process, revealing that honest mining remains dominant even with 20% of total hashrate.

Contribution

It introduces a stochastic model for gamma in rogue mining strategies using Markov analysis, providing new insights into profitability dynamics.

Findings

Honest mining remains dominant with 20% hashrate.

Stochastic modeling of gamma offers more accurate profitability analysis.

Numerical distribution matches observed network behavior.

Abstract

Many of the recent works on the profitability of rogue mining strategies hinge on a parameter called $\gamma$ that measures the proportion of the honest network attracted by the attacker to mine on top of his fork. These works, see arXiv:1808.01041 and arXiv.1805.08281, have surmised conclusions based on premises that erroneously treat $\gamma$ to be constant. In this paper, we treat $\gamma$ as a stochastic process and attempt to find its distribution through a Markov analysis. We begin by making strong assumptions on gamma's behaviour and proceed to translate them mathematically in order to apply them in a Markov setting. The aforementioned is executed in two separate occasions for two different models. Furthermore, we model the Bitcoin network and numerically derive a limiting distribution whereby the relative accuracy of our models is tested through a likelihood analysis. Finally, we conclude that even with control of 20% of the total hashrate, honest mining is the strongly dominant strategy.