Strangely mined bitcoins: Empirical analysis of anomalies in the bitcoin blockchain transaction network.

The blockchain technology introduced by bitcoin, with its decentralised peer-to-peer network and cryptographic protocols, provides a public and accessible database of bitcoin transactions that have attracted interest from both economics and network science as an example of a complex evolving monetar...

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Autores principales:	María Óskarsdóttir, Jacky Mallett
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/fff20cbc98ba4186abf57c18a0f718d7
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spelling	oai:doaj.org-article:fff20cbc98ba4186abf57c18a0f718d72021-12-02T20:13:54ZStrangely mined bitcoins: Empirical analysis of anomalies in the bitcoin blockchain transaction network.1932-620310.1371/journal.pone.0258001https://doaj.org/article/fff20cbc98ba4186abf57c18a0f718d72021-01-01T00:00:00Zhttps://doi.org/10.1371/journal.pone.0258001https://doaj.org/toc/1932-6203The blockchain technology introduced by bitcoin, with its decentralised peer-to-peer network and cryptographic protocols, provides a public and accessible database of bitcoin transactions that have attracted interest from both economics and network science as an example of a complex evolving monetary network. Despite the known cryptographic guarantees present in the blockchain, there exists significant evidence of inconsistencies and suspicious behavior in the chain. In this paper, we examine the prevalence and evolution of two types of anomalies occurring in coinbase transactions in blockchain mining, which we reported on in earlier research. We further develop our techniques for investigating the impact of these anomalies on the blockchain transaction network, by building networks induced by anomalous coinbase transactions at regular intervals and calculating a range of network measures, including degree correlation and assortativity, as well as inequality in terms of wealth and anomaly ratio using the Gini coefficient. We obtain time series of network measures calculated over the full transaction network and three sub-networks. Inspecting trends in these time series allows us to identify a period in time with particularly strange transaction behavior. We then perform a frequency analysis of this time period to reveal several blocks of highly anomalous transactions. Our technique represents a novel way of using network science to detect and investigate cryptographic anomalies.María ÓskarsdóttirJacky MallettPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 16, Iss 9, p e0258001 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q María Óskarsdóttir Jacky Mallett Strangely mined bitcoins: Empirical analysis of anomalies in the bitcoin blockchain transaction network.
description	The blockchain technology introduced by bitcoin, with its decentralised peer-to-peer network and cryptographic protocols, provides a public and accessible database of bitcoin transactions that have attracted interest from both economics and network science as an example of a complex evolving monetary network. Despite the known cryptographic guarantees present in the blockchain, there exists significant evidence of inconsistencies and suspicious behavior in the chain. In this paper, we examine the prevalence and evolution of two types of anomalies occurring in coinbase transactions in blockchain mining, which we reported on in earlier research. We further develop our techniques for investigating the impact of these anomalies on the blockchain transaction network, by building networks induced by anomalous coinbase transactions at regular intervals and calculating a range of network measures, including degree correlation and assortativity, as well as inequality in terms of wealth and anomaly ratio using the Gini coefficient. We obtain time series of network measures calculated over the full transaction network and three sub-networks. Inspecting trends in these time series allows us to identify a period in time with particularly strange transaction behavior. We then perform a frequency analysis of this time period to reveal several blocks of highly anomalous transactions. Our technique represents a novel way of using network science to detect and investigate cryptographic anomalies.
format	article
author	María Óskarsdóttir Jacky Mallett
author_facet	María Óskarsdóttir Jacky Mallett
author_sort	María Óskarsdóttir
title	Strangely mined bitcoins: Empirical analysis of anomalies in the bitcoin blockchain transaction network.
title_short	Strangely mined bitcoins: Empirical analysis of anomalies in the bitcoin blockchain transaction network.
title_full	Strangely mined bitcoins: Empirical analysis of anomalies in the bitcoin blockchain transaction network.
title_fullStr	Strangely mined bitcoins: Empirical analysis of anomalies in the bitcoin blockchain transaction network.
title_full_unstemmed	Strangely mined bitcoins: Empirical analysis of anomalies in the bitcoin blockchain transaction network.
title_sort	strangely mined bitcoins: empirical analysis of anomalies in the bitcoin blockchain transaction network.
publisher	Public Library of Science (PLoS)
publishDate	2021
url	https://doaj.org/article/fff20cbc98ba4186abf57c18a0f718d7
work_keys_str_mv	AT mariaoskarsdottir strangelyminedbitcoinsempiricalanalysisofanomaliesinthebitcoinblockchaintransactionnetwork AT jackymallett strangelyminedbitcoinsempiricalanalysisofanomaliesinthebitcoinblockchaintransactionnetwork
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Strangely mined bitcoins: Empirical analysis of anomalies in the bitcoin blockchain transaction network.

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