Stabl: Blockchain Fault Tolerance

TL;DR

This paper evaluates the fault tolerance of five modern blockchain systems by injecting failures and analyzing their resilience, revealing significant vulnerabilities and the impact of Byzantine fault tolerance mechanisms.

Contribution

It introduces a novel sensitivity metric and provides an empirical assessment of blockchain fault tolerance through controlled failure injections.

Findings

Most blockchains are highly impacted by small network failures.

Redbelly and Avalanche benefit from Byzantine fault tolerance redundancy.

Avalanche and Solana cannot recover from localized transient failures.

Abstract

Blockchain promises to make online services more fault tolerant due to their inherent distributed nature. Their ability to execute arbitrary programs in different geo-distributed regions and on diverse operating systems make them an alternative of choice to our dependence on unique software whose recent failure affected 8.5 millions of machines. As of today, it remains, however, unclear whether blockchains can truly tolerate failures. In this paper, we assess the fault tolerance of blockchain. To this end, we inject failures in controlled deployments of five modern blockchain systems, namely Algorand, Aptos, Avalanche, Redbelly and Solana. We introduce a novel sensitivity metric, interesting in its own right, as the difference between the integrals of two cumulative distribution functions, one obtained in a baseline environment and one obtained in an adversarial environment. Our results indicate that (i) all blockchains except Redbelly are highly impacted by the failure of a small part of their network, (ii) Avalanche and Redbelly benefit from the redundant information needed for Byzantine fault tolerance while others are hampered by it, and more dramatically (iii) Avalanche and Solana cannot recover from localised transient failures.