The Complex Community Structure of the Bitcoin Address Correspondence\n Network

Abstract

Bitcoin is built on a blockchain, an immutable decentralised ledger that\nallows entities (users) to exchange Bitcoins in a pseudonymous manner. Bitcoins\nare associated with alpha-numeric addresses and are transferred via\ntransactions. Each transaction is composed of a set of input addresses\n(associated with unspent outputs received from previous transactions) and a set\nof output addresses (to which Bitcoins are transferred). Despite Bitcoin was\ndesigned with anonymity in mind, different heuristic approaches exist to detect\nwhich addresses in a specific transaction belong to the same entity. By\napplying these heuristics, we build an Address Correspondence Network: in this\nrepresentation, addresses are nodes are connected with edges if at least one\nheuristic detects them as belonging to the same entity. %addresses are nodes\nand edges are drawn between addresses detected as belonging to the same entity\nby at least one heuristic. %nodes represent addresses and edges model the\nlikelihood that two nodes belong to the same entity %In this network, connected\ncomponents represent sets of addresses controlled by the same entity. In this\npaper, we analyse for the first time the Address Correspondence Network and\nshow it is characterised by a complex topology, signalled by a broad, skewed\ndegree distribution and a power-law component size distribution. Using a\nlarge-scale dataset of addresses for which the controlling entities are known,\nwe show that a combination of external data coupled with standard community\ndetection algorithms can reliably identify entities. The complex nature of the\nAddress Correspondence Network reveals that usage patterns of individual\nentities create statistical regularities; and that these regularities can be\nleveraged to more accurately identify entities and gain a deeper understanding\nof the Bitcoin economy as a whole.\n