Complex Network Analysis of the Bitcoin Transaction Network

TL;DR

This paper applies complex network analysis to the Bitcoin transaction network, introducing a new sampling method and revealing key structural properties that inform future security and fraud detection strategies.

Contribution

It introduces the random walk with flying-back (RWFB) sampling method and provides a comprehensive analysis of Bitcoin's network structure.

Findings

Bitcoin network exhibits small-world properties

Presence of multi-center structure in the network

Preferential attachment and non-rich-club characteristics

Abstract

In this brief, we conduct a complex-network analysis of the Bitcoin transaction network. In particular, we design a new sampling method, namely random walk with flying-back (RWFB), to conduct effective data sampling. We then conduct a comprehensive analysis of the Bitcoin network in terms of the degree distribution, clustering coefficient, the shortest-path length, connected component, centrality, assortativity, and the rich-club coefficient. We obtain several important observations including the small-world phenomenon, multi-center status, preferential attachment, and non-rich-club effect of the current network. This work brings up an in-depth understanding of the current Bitcoin blockchain network and offers implications for future directions in malicious activity and fraud detection in cryptocurrency blockchain networks.