A Game-Theoretic Approach to the Study of Blockchain's Robustness

TL;DR

This paper uses game theory to analyze and improve the robustness of Ethereum Proof-of-Stake blockchains, focusing on safety, liveness, and incentive mechanisms to prevent vulnerabilities and malicious behavior.

Contribution

It introduces a combined distributed systems and game-theoretic framework to evaluate Ethereum PoS robustness and identifies incentive-based vulnerabilities.

Findings

Inactivity leak mechanism affects safety and liveness balance.

Rational validator strategies can threaten protocol robustness.

Incentive design is crucial for resilient blockchain protocols.

Abstract

Blockchains have sparked global interest in recent years, gaining importance as they increasingly influence technology and finance. This thesis investigates the robustness of blockchain protocols, specifically focusing on Ethereum Proof-of-Stake. We define robustness in terms of two critical properties: Safety, which ensures that the blockchain will not have permanent conflicting blocks, and Liveness, which guarantees the continuous addition of new reliable blocks. Our research addresses the gap between traditional distributed systems approaches, which classify agents as either honest or Byzantine (i.e., malicious or faulty), and game-theoretic models that consider rational agents driven by incentives. We explore how incentives impact the robustness with both approaches. The thesis comprises three distinct analyses. First, we formalize the Ethereum PoS protocol, defining its properties and examining potential vulnerabilities through a distributed systems perspective. We identify that certain attacks can undermine the system's robustness. Second, we analyze the inactivity leak mechanism, a critical feature of Ethereum PoS, highlighting its role in maintaining system liveness during network disruptions but at the cost of safety. Finally, we employ game-theoretic models to study the strategies of rational validators within Ethereum PoS, identifying conditions under which these agents might deviate from the prescribed protocol to maximize their rewards. Our findings contribute to a deeper understanding of the importance of incentive mechanisms for blockchain robustness and provide insights into designing more resilient blockchain protocols.