Towards open data blockchain analytics: a Bitcoin perspective

Abstract

Bitcoin is the first implementation of a technology that has become known as a ‘public permissionless’ blockchain. Such systems allow public read/write access to an append-only blockchain database without the need for any mediating central authority. Instead, they guarantee access, security and protocol conformity through an elegant combination of cryptographic assurances and game theoretic economic incentives. Not until the advent of the Bitcoin blockchain has such a trusted, transparent, comprehensive and granular dataset of digital economic behaviours been available for public network analysis. In this article, by translating the cumbersome binary data structure of the Bitcoin blockchain into a high fidelity graph model, we demonstrate through various analyses the often overlooked social and econometric benefits of employing such a novel open data architecture. Specifically, we show: (i) how repeated patterns of transaction behaviours can be revealed to link user activity across the blockchain; (ii) how newly mined bitcoin can be associated to demonstrate individual accumulations of wealth; (iii) through application of the naïve quantity theory of money that Bitcoin's disinflationary properties can be revealed and measured; and (iv) how the user community can develop coordinated defences against repeated denial of service attacks on the network. Such public analyses of this open data are exemplary benefits unavailable to the closed data models of the ‘private permissioned’ distributed ledger architectures currently dominating enterprise-level blockchain development owing to existing issues of scalability, confidentiality and governance.

Characterizing Entities in the Bitcoin Blockchain

“…A different type of attack is presented in [20], where the authors show that statistical analysis of bloom filters could help to identify the set of addresses owned by Bitcoin wallets. It has also been shown that patterns of newly minted bitcoins could play a role in revealing information of certain Bitcoin users [15].…”

Applying the ETL Process to Blockchain Data. Prospect and Findings

“…More recently, researchers started a systematic investigation on Bitcoin user interrelations [10] and habits, i.e., the address usage and their strategies to improve the anonymization [2,3], vulnerabilities [11][12][13], and so on, and to allow forensic investigations, to, for instance, identify the origin of scams and illegal activities, such as the case of the blackmail WannaCry, with which criminals required Bitcoin payments to unlock the victim machines [4,5,14].…”

An overview of blockchain science and engineering

“…For sake of illustration, let us now sketch the contributions of some of the papers in this special issue. The paper by McGinn et al [15] argues and demonstrates that the combination of data analytics and data visualization offers a powerful tool box for understanding behaviours and trends on open, permissionless blockchains-here illustrated on Bitcoin.…”