Selfish Mining in Multi-Attacker Scenarios: An Empirical Evaluation of Nakamoto, Fruitchain, and Strongchain

TL;DR

This paper presents an empirical evaluation of selfish mining attacks involving multiple attackers across different blockchain consensus protocols, introducing a simulation framework to analyze and compare their security thresholds.

Contribution

It introduces a stochastic simulation framework for analyzing selfish mining with multiple attackers across various protocols, including Nakamoto, Fruitchain, and Strongchain, and discovers new attack thresholds.

Findings

Verified existing thresholds in literature

Discovered novel thresholds for multiple attackers

Provided open-source framework for future research

Abstract

The aim of this work is to enhance blockchain security by deepening the understanding of selfish mining attacks in various consensus protocols, especially the ones that have the potential to mitigate selfish mining. Previous research was mainly focused on a particular protocol with a single selfish miner, while only limited studies have been conducted on two or more attackers. To address this gap, we proposed a stochastic simulation framework that enables analysis of selfish mining with multiple attackers across various consensus protocols. We created the model of Proof-of-Work (PoW) Nakamoto consensus (serving as the baseline) as well as models of two additional consensus protocols designed to mitigate selfish mining: Fruitchain and Strongchain. Using our framework, thresholds reported in the literature were verified, and several novel thresholds were discovered for 2 and more attackers. We made the source code of our framework available, enabling researchers to evaluate any newly added protocol with one or more selfish miners and cross-compare it with already modeled protocols.