학술논문

Revisiting Nakamoto Consensus in Asynchronous Networks: A Comprehensive Analysis of Bitcoin Safety and Chain Quality
Document Type
Periodical
Source
IEEE/ACM Transactions on Networking IEEE/ACM Trans. Networking Networking, IEEE/ACM Transactions on. 32(1):844-858 Feb, 2024
Subject
Communication, Networking and Broadcast Technologies
Computing and Processing
Signal Processing and Analysis
Bitcoin
Blockchains
Safety
Peer-to-peer computing
Propagation delay
Delays
Security
Nakamoto consensus
Bitcoin partitioning
Language
ISSN
1063-6692
1558-2566
Abstract
The Bitcoin blockchain safety relies on strong network synchrony. Therefore, violating the blockchain safety requires strong adversaries that control a mining pool with ≈51% hash rate. In this paper, we show that the network synchrony does not hold in the real world Bitcoin network which can be exploited to feasibly violate the blockchain safety and chain quality. Towards that, first we construct the Bitcoin ideal functionality to formally specify its ideal execution model in a synchronous network. We then develop a large-scale data collection system through which we connect with more than 103K IP addresses of the Bitcoin nodes and identify 871 mining nodes. We contrast the ideal functionality against the real world measurements to expose the network anomalies that can be exploited to optimize the existing attacks. Particularly, we observe a non-uniform block propagation pattern among the mining nodes showing that the Bitcoin network is asynchronous in practice. To realize the threat of an asynchronous network, we present the HashSplit attack that allows an adversary to orchestrate concurrent mining on multiple branches of the blockchain to violate common prefix and chain quality properties. We also propose the attack countermeasures by tweaking Bitcoin Core to model the Bitcoin ideal functionality. Our measurements, theoretical modeling, proposed attack, and countermeasures open new directions in the security evaluation of Bitcoin and similar blockchain systems.