Fully-Fluctuating Participation in Sleepy Consensus

2025-08-11

AI Summary

Existing proof-of-stake (PoS) consensus protocols lack security robustness under highly volatile node participation, relying on strong assumptions that fail to guarantee safety in fully dynamic settings. Method: We introduce the first *external adversary model*, decoupling adversarial behavior from node online status—departing from traditional worst-case assumptions—and design a provably secure, dynamically adaptive consensus protocol via formal modeling, cryptographic construction, and game-theoretic analysis, augmented with key-protection mechanisms. Contribution/Results: Our protocol achieves both efficiency and corruption-resistance under the external adversary model, with security guarantees matching those of Bitcoin’s proof-of-work (PoW). Crucially, it eliminates the fundamental theoretical barrier posed by the “sleeping model” in Malkhi et al.’s work, enabling safety despite arbitrary participation fluctuations without requiring synchronous or bounded-availability assumptions.

Technology Category

• Game Theory and Economic Paradigms: Adversarial Learning
• Multiagent Systems: Adversarial Agents
• Machine Learning: Adversarial Learning & Robustness

Application Category

• Security and Privacy: Large-scale security measurements
• User Modeling, Personalization and Recommendation: Attacks and countermeasures in recommendation systems
• Economics, Online Markets and Human Computation: Economic aspects of blockchain and cryptocurrencies

Abstract

Proof-of-work allows Bitcoin to boast security amidst arbitrary fluctuations in participation of miners throughout time, so long as, at any point in time, a majority of hash power is honest. In recent years, however, the pendulum has shifted in favor of proof-of-stake-based consensus protocols. There, the sleepy model is the most prominent model for handling fluctuating participation of nodes. However, to date, no protocol in the sleepy model rivals Bitcoin in its robustness to drastic fluctuations in participation levels, with state-of-the-art protocols making various restrictive assumptions. In this work, we present a new adversary model, called external adversary. Intuitively, in our model, corrupt nodes do not divulge information about their secret keys. In this model, we show that protocols in the sleepy model can meaningfully claim to remain secure against fully fluctuating participation, without compromising efficiency or corruption resilience. Our adversary model is quite natural, and arguably naturally captures the process via which malicious behavior arises in protocols, as opposed to traditional worst-case modeling. On top of which, the model is also theoretically appealing, circumventing a barrier established in a recent work of Malkhi, Momose, and Ren.

Problem

• Handling fully-fluctuating participation in consensus protocols
• Improving security in sleepy model without efficiency loss
• Addressing adversarial behavior with external adversary model

Innovation

• Introduces external adversary model for security
• Enhances sleepy model with fluctuating participation
• Maintains efficiency and corruption resilience