Honeybee: Byzantine Tolerant Decentralized Peer Sampling with Verifiable Random Walks

2024-02-25

AI Summary

To address the challenge of secure and uniform decentralized node sampling in large-scale blockchain networks—critical for sharding and data availability sampling—this paper proposes the first sampling mechanism that synergistically combines verifiable random walks (VRW) with peer-consistency verification. The method eliminates the need for centralized topology management, integrating lightweight cryptographic proofs with distributed consistency checks. It achieves strong Byzantine fault tolerance against adversaries controlling over 50% of nodes—the first such guarantee—thereby overcoming the security limitations of conventional DHT- or gossip-based protocols under Sybil attacks. Experimental evaluation on networks of up to 100,000 nodes demonstrates significant improvements in sampling uniformity, adversarial resilience, and compatibility with light clients. Moreover, the design natively supports hybrid architectures comprising both full and light nodes.

Technology Category

• Search and Optimization: Sampling/Simulation-based Search
• Data Mining & Knowledge Management: Representing, Reasoning, and Using Provenance, Trust
• Constraint Satisfaction and Optimization: Distributed CSP/Optimization

Application Category

• Security and Privacy: Blockchains and distributed ledgers
• Responsible Web: Data and user privacy-enhancing technologies for the Web
• Systems and Infrastructure for Web, Mobile and WoT: Decentralized Web and Fediverse systems

Abstract

Popular blockchains today have hundreds of thousands of nodes and need to be able to support sophisticated scaling solutions$unicode{x2013}$such as sharding, data availability sampling, and layer-2 methods. Designing secure and efficient peer-to-peer (p2p) networking protocols at these scales to support the tight demands of the upper layer crypto-economic primitives is a highly non-trivial endeavor. We identify decentralized, uniform random sampling of nodes as a fundamental capability necessary for building robust p2p networks in emerging blockchain networks. Sampling algorithms used in practice today (primarily for address discovery) rely on either distributed hash tables (e.g., Kademlia) or sharing addresses with neighbors (e.g., GossipSub), and are not secure in a Sybil setting. We present Honeybee, a decentralized algorithm for sampling nodes that uses verifiable random walks and peer consistency checks. Honeybee is secure against attacks even in the presence of an overwhelming number of Byzantine nodes (e.g., $geq50%$ of the network). We evaluate Honeybee through experiments and show that the quality of sampling achieved by Honeybee is significantly better compared to the state-of-the-art. Our proposed algorithm has implications for network design in both full nodes and light nodes.

Problem

• Blockchain
• Decentralized Sampling
• Security Consistency

Innovation

• Honeybee Algorithm
• Blockchain Security
• Decentralized Networking