Quantifying Liveness and Safety of Avalanche's Snowball

TL;DR

This work examines the resilience properties of the Snowball and Avalanche protocols that underlie the popular Avalanche blockchain and concludes that Snowball and Avalanche are akin to Byzantine reliable broadcast protocols as opposed to consensus.

Abstract

This work examines the resilience properties of the Snowball and Avalanche protocols that underlie the popular Avalanche blockchain. We experimentally quantify the resilience of Snowball using a simulation implemented in Rust, where the adversary strategically rebalances the network to delay termination. We show that in a network of $n$ nodes of equal stake, the adversary is able to break liveness when controlling $Ω(\sqrt{n})$ nodes. Specifically, for $n = 2000$, a simple adversary controlling $5.2\%$ of stake can successfully attack liveness. When the adversary is given additional information about the state of the network (without any communication or other advantages), the stake needed for a successful attack is as little as $2.8\%$. We show that the adversary can break safety in time exponentially dependent on their stake, and inversely linearly related to the size of the network, e.g. in 265 rounds in expectation when the adversary controls $25\%$ of a network of 3000. We conclude that Snowball and Avalanche are akin to Byzantine reliable broadcast protocols as opposed to consensus.

Figures (4)

• Figure 1: Snowball algorithm.
• Figure 2: Adversary strategy for liveness attack.
• Figure 3: Minimum fraction of stake needed by the adversary to successfully attack liveness, plotted against the number of nodes in the network with equal stake.
• Figure 4: Adversary strategy for safety attack.

Theorems & Definitions (2)

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