Robust P2P networking connectivity estimation engine for permissionless Bitcoin cryptocurrency

• Published in: Computer networks (Amsterdam, Netherlands : 1999) Netherlands : 1999), 2022-12, Vol.219, p.109436, Article 109436
• Main Authors: Hong, Hsiang-Jen, Fan, Wenjun, Wuthier, Simeon, Kim, Jinoh, Chow, C. Edward, Zhou, Xiaobo, Chang, Sang-Yoon
• Format: Article
• Language: English
• Subjects: Bitcoin; Blockchain; Cryptocurrency; Peer-to-peer networking; Permissionless; Robustness
• ISSN: 1389-1286; 1872-7069
• DOI: 10.1016/j.comnet.2022.109436

Blockchain relies on the underlying peer-to-peer (P2P) networking to broadcast and get up-to-date on the blocks and transactions. Because of the blockchain operations’ reliance on the information provided by P2P networking, it is imperative to have high P2P connectivity for the quality of the blockchain system operations and performances. High P2P networking connectivity ensures that a peer node is connected to multiple other peers providing a diverse set of observers of the current state of the blockchain and transactions. However, in a permissionless Bitcoin cryptocurrency network, using the peer identifiers – including the current approach of counting the number of distinct IP addresses and port numbers – can be ineffective in measuring the number of peer connections and estimating the networking connectivity. Such current approach is further challenged by the networking threats manipulating identities. We build a robust estimation engine for the P2P networking connectivity by sensing and processing the P2P networking traffic. We take a systematic approach to study our engine and analyze the followings: the different components of the connectivity estimation engine and how they affect the accuracy performances, the role and the effectiveness of an outlier detection to enhance the connectivity estimation, and the engine’s interplay with the Bitcoin protocol. We implement a working Bitcoin prototype connected to the Bitcoin mainnet to validate and improve our engine’s performances and evaluate the estimation accuracy and cost efficiency of our connectivity estimation engine. Our results show that our scheme effectively counters the identity-manipulations threats, achieves 96.4% estimation accuracy with a tolerance of one peer connection, and is lightweight in the overheads in the mining rate, thus making it appropriate for the miner deployment. •The current Bitcoin nodes are vulnerable to threats manipulating the peer identities.•Design our connectivity estimation engine by analyzing real-world Bitcoin traffic.•Examine the useful networking-sensor parameters for our connectivity estimation.•Involve an outlier detection to determine the viability of connectivity estimation.•The result shows our engine is robust against threats based on identity manipulations.