Blockchain and distributed ledger technologies are disrupting the world as we know it. Cryptocurrencies are increasingly been adopted not only by a large number of retail investors but financial institutions and even countries are embracing them. Nonetheless, there is a significant number and types of cryptocurrencies and, their treatment will likely depend on their legal status, use, and nature. Some jurisdictions may equate the legal status of cryptocurrencies to commodities or property, others may consider them to be digital currencies or legal tenders, while others may treat them as securities, financial instruments, or as a different asset class such as digital assets. Consequently, countries may regulate a cryptocurrency in different legal categories and might be overseen by a range of authorities depending on their use case and nature. This article aspires to shed some light on legal grey areas by studying how cryptocurrencies are regulated in a variety of jurisdictions and how their legal status is defined.
Cryptocurrencies differ from traditional financial assets as they are not governed by any higher authority, have no physical representation, are indefinitely divisible, and are not based on any tangible assets or country. While their popularity and use have surged over the years, they are still subject to an underlying risk. The purpose of this research is to investigate the regulatory approach for cryptocurrencies adopted around the world. To achieve the purpose of this research, extant literature is examined using a systematic literature review. Using a total of 49 Scopus indexed shortlisted articles, the extant literature on the various risks related to cryptocurrency and the regulatory approach adopted for the same was explored. The prior literature was classified into four thematic clusters of the regulatory approach to risks: pandemic, volatility, money laundering and cyber security. The findings suggest the regulations governing cryptocurrency are still at an infancy stage, and it still suffers from the challenge of limited transparency. The pandemic did not have a drastic impact on cryptocurrency. Cryptocurrencies are volatile in reaction to economic policy uncertainty and macroeconomic variables. To the best of the authorâs knowledge, this review paper is one of the few contributing to the gaps in the literature on the various risks and their associated regulatory approach to managing cryptocurrency.
The impact of globalization and the growing digitalization of the economy is becoming increasingly felt in the area of economic criminality, and we therefore believe that it is a matter of urgency to seek viable and effective solutions to manage this area of concerns, thus preventing the contamination of the borderline that currently separates legal and illegal technologies, depending on how they are regulated or not. In this light, the aim of our paper is to explore those instances in which blockchain accounting has the potential to be a viable solution to guarantee the security and legality of economic and financial transactions, thereby significantly mitigating the impact and frequency of economic criminality. The main objectives we pursue are to define the nature of the interrelation among the concept of blockchain, accounting and economic criminality and to evaluate the potential advantages of implementing blockchain technology in the accounting system. The main findings are a comprehensive mapping of the network that links blockchain technology, accounting and economic criminality employing the clustering method. These are likely to be of valuable assistance not only for the legislator, but also for the shaping of future research paths in this field and, last but not least, for an essential group of stakeholders such as computer scientists, accountants, auditors and national governments.
Abstract The rise of digital currencies challenges practices of monetary sovereignty and impacts the international monetary order. Drawing on recent IPE debates about the publicâprivate nature of money, the critique of the âimpossible trinityâ and âterritorial currencies,â this article explores the competition between China and the United States over and within the international monetary system. The two largest economies display strikingly divergent regulatory approaches to cryptocurrencies and Central Bank Digital Currency (CBDC). China completely banned cryptocurrencies but became a frontârunner in developing a CBDC. It aims to expand the RMB's global role without giving up its monetary control. U.S. administrations have instead reluctantly considered regulating cryptocurrencies. Discussions on a potential digital U.S. dollar (USD) only began in 2020. Washington aims at preserving the existing crossâborder financial mechanisms and offshore infrastructure for USDâdenominated transactions and credit creation. It focuses on financial crime and maintaining the innovation dynamic of its private sector to preserve its âexorbitant privilege.â Emerging financial infrastructures and standards for digital currencies are the new technological arena for U.S.âChina monetary competition.
Gibran GĂłmez, Pedro Moreno-SĂĄnchez, Juan Antonio Caballero-HernĂĄndez
Cybercriminals often leverage Bitcoin for their illicit activities. In this work, we propose back-and-forth exploration, a novel automated Bitcoin transaction tracing technique to identify cybercrime financial relationships. Given seed addresses belonging to a cybercrime campaign, it outputs a transaction graph, and identifies paths corresponding to relationships between the campaign under study and external services and other cybercrime campaigns. Back-and-forth exploration provides two key contributions. First, it explores both forward and backwards, instead of only forward as done by prior work, enabling the discovery of relationships that cannot be found by only exploring forward (e.g., deposits from clients of a mixer). Second, it prevents graph explosion by combining a tagging database with a machine learning classifier for identifying addresses belonging to exchanges. We evaluate back-and-forth exploration on 30 malware families. We build oracles for 4 families using Bitcoin for C&C and use them to demonstrate that back-and-forth exploration identifies 13 C&C signaling addresses missed by prior work, 8 of which are fundamentally missed by forward-only explorations. Our approach uncovers a wealth of services used by the malware including 44 exchanges, 11 gambling sites, 5 payment service providers, 4 underground markets, 4 mining pools, and 2 mixers. In 4 families, the relations include new attribution points missed by forward-only explorations. It also identifies relationships between the malware families and other cybercrime campaigns, highlighting how some malware operators participate in a variety of cybercriminal activities.
El Salvador has adopted Bitcoin as legal tender. This article provides a critical evaluation of the countryâs Bitcoin initiative and its economic and social impacts.
Peter FratriÄ, Giovanni Sileno, S. Klous, Tom van Engers
Fraudulent actions of a trader or a group of traders can cause substantial disturbance to the market, both directly influencing the price of an asset or indirectly by misinforming other market participants. Such behavior can be a source of systemic risk and increasing distrust for the market participants, consequences that call for viable countermeasures. Building on the foundations provided by the extant literature, this study aims to design an agent-based market model capable of reproducing the behavior of the Bitcoin market during the time of an alleged Bitcoin price manipulation that occurred between 2017 and early 2018. The model includes the mechanisms of a limit order book market and several agents associated with different trading strategies, including a fraudulent agent, initialized from empirical data and who performs market manipulation. The model is validated with respect to the Bitcoin price as well as the amount of Bitcoins obtained by the fraudulent agent and the traded volume. Simulation results provide a satisfactory fit to historical data. Several price dips and volume anomalies are explained by the actions of the fraudulent trader, completing the known body of evidence extracted from blockchain activity. The model suggests that the presence of the fraudulent agent was essential to obtain Bitcoin price development in the given time period; without this agent, it would have been very unlikely that the price had reached the heights as it did in late 2017. The insights gained from the model, especially the connection between liquidity and manipulation efficiency, unfold a discussion on how to prevent illicit behavior.
George Kappos, Haaroon Yousaf, Rainer Stßtz, S. Rollet ¡ 6 authors
One of the defining features of Bitcoin and the thousands of cryptocurrencies that have been derived from it is a globally visible transaction ledger. While Bitcoin uses pseudonyms as a way to hide the identity of its participants, a long line of research has demonstrated that Bitcoin is not anonymous. This has been perhaps best exemplified by the development of clustering heuristics, which have in turn given rise to the ability to track the flow of bitcoins as they are sent from one entity to another. In this paper, we design a new heuristic that is designed to track a certain type of flow, called a peel chain, that represents many transactions performed by the same entity; in doing this, we implicitly cluster these transactions and their associated pseudonyms together. We then use this heuristic to both validate and expand the results of existing clustering heuristics. We also develop a machine learning-based validation method and, using a ground-truth dataset, evaluate all our approaches and compare them with the state of the art. Ultimately, our goal is to not only enable more powerful tracking techniques but also call attention to the limits of anonymity in these systems.
The disruptive impact of blockchain technologies can be felt across numerous industries as it threatens to disrupt existing business models and economic structures. To better understand this impact, academic researchers regularly apply well-established theories and methods. The vast majority of these approaches are based on multivariate methods that rely on average behavior and treat extreme cases as outliers. However, as recent history has shown, current developments in blockchain and cryptocurrencies are frequently characterized by aberrant behavior and unexpected events that shape individualsâ perceptions, market behavior, and public policymaking. In this paper, I apply various scenario tools to identify such extreme scenarios and illustrate their underlying structure as bundles of interdependent factors. Using the case of Bitcoin, I illustrate that the identification of extreme positive and negative scenarios is complex and heavily depends on underlying economic assumptions. I present three scenarios in which Bitcoin is characterized as a financial savior, as a severe threat to economic stability, or as a substitute to overcome several shortcomings of the existing financial system. The research questions that can be derived from these scenarios bridge behavioral and design science research and provide a fertile ground for impactful future research.
Decentralized finance (DeFi) in Ethereum is a financial ecosystem built on the blockchain that has locked over 200 billion USD until April 2022. All transaction information is transparent and open when transacting through the DeFi protocol, which has led to a series of attacks. Several studies have attempted to optimize it from both economic and technical perspectives. However, few works analyze the vulnerabilities and optimizations of the entire DeFi system. In this paper, we first systematically analyze vulnerabilities related to DeFi in Ethereum at several levels, then we investigate real-world attacks. Finally, we summarize the achievements of DeFi optimization and provide some future directions.
Currency dominance has been the symbol of national power, influence, and dominance. After the Second World War, the Dollar has maintained its unrivaled influence as a currency reserve by central banks and as a global transaction currency. Recently, cryptocurrency and the distributed ledger system were seen as a challenge. However, due to the challenge it poses to the sovereignty of nation-states, central banks have resorted to developing the central bank digital currencies (CBDCs). China is the only major economy to have tested a CBDC, a symbol of its increasing economic power and innovation. Contrary to Mearsheimerâs theory of offensive realism, developments show that China can use its offensive economic capabilities to build a regional order through the belt and road initiative (BRI). With the recent release of its Central Bank Electronic Payment and the Blockchain-based Network System, China can seek to regionalize the use of its renminbi (RMB) and rival the power of the Dollar.
O artigo tem como elemento central o estudo dos reflexos da adoção de smart contracts nas relaçþes privadas. O trabalho concentra sua abordagem na possibilidade de esvaziamento das formas de jurisdição tradicionais, pela caracterĂstica da auto executoriedade das clĂĄusulas contratuais, como consequĂŞncia da utilização da tecnologia blockchain. A tecnologia blockchain vem se tornando um dos maiores protagonistas na transformação das tecnologias digitais e isso se deve a sua peculiar caracterĂstica de gestĂŁo descentralizada das informaçþes, alĂŠm de sua confiabilidade. A anĂĄlise parte da identificação dos elementos intrĂnsecos dos smart contracts, demonstrando, de maneira dedutiva, suas especificidades e seus pontos de intersecção com a teoria contratual tradicional. Com a ampliação da utilização dos smart contracts para regular cada vez mais situaçþes da vida privada, estabeleceu-se a necessidade de incorporar um elemento exĂłgeno ao sistema, que ĂŠ a figura do orĂĄculo, cuja função ĂŠ alimentar com dados externos a blockchain. Tem-se, portanto, um elo entre o mundo fenomĂŞnico e o mundo puramente virtual, atravĂŠs da tecnologia blockchain. Desse modo, a partir da concepção do orĂĄculo, abre-se a possibilidade de ligação entre a jurisdição e os smart contracts.
The âBitcoin Generator Scamâ (BGS) is a cyberattack in which scammers promise to provide victims with free cryptocurrencies in exchange for a small mining fee. In this paper, we present a data-driven system to detect, track, and analyze the BGS. It works as follows: we first formulate search queries related to BGS and use search engines to find potential instances of the scam. We then use a crawler to access these pages and a classifier to differentiate actual scam instances from benign pages. Last, we automatically monitor the BGS instances to extract the cryptocurrency addresses used in the scam. A unique feature of our system is that it proactively searches for and detects the scam pages. Thus, we can find addresses that have not yet received any transactions. Our data collection project spanned 16 months, from November 2019 to February 2021. We uncovered more than 8,000 cryptocurrency addresses directly associated with the scam, hosted on over 1,000 domains. Overall, these addresses have received around 8.7 million USD, with an average of 49.24 USD per transaction. Over 70% of the active addresses that we are capturing are detected before they receive any transactions, that is, before anyone is victimized. We also present some post-processing analysis of the dataset that we have captured to aggregate attacks that can be reasonably confidently linked to the same attacker or group. Our system is one of the first academic feeds to the APWG eCrime Exchange database. It has been actively and automatically feeding the database since November 2020.
There is growing debate over whether applications of blockchain and other financial technologies (âfintechsâ) reinforce forms of neo-colonial extraction that perpetuate NorthâSouth inequities or help enact decolonial ambitions across the Global South. This paper expands such discussions and contributes to this special issue on âfintech in Africaâ by situating emerging African blockchain techno-experimentation within wider international infrastructural relations. We argue that blockchain-based activities in and across the African continent must be understood within those also unfolding in countries that have been subjected to financial sanctions of varying types (China, Iran, Russia, Venezuela) by the European Union, United States, and United Nations. Our analysis traces how blockchain-based applications by sanctioned countries are extending exclusions in novel and existing socio-technical relations. We conclude that blockchain-based experiments are facilitating rather than displacing a colonial finance/security infrastructure.
Ardeshir Shojaeinasab, Amir Pasha Motamed, Behnam Bahrak
Abstract Cryptocurrencies, particularly Bitcoin, have garnered attention for their potential in anonymous transactions. However, their anonymity has often been compromised by deanonymization attacks. To counter this, mixing services have been introduced. While they enhance privacy, they obscure fund traceability. This study seeks to demystify transactions linked to these services, shedding light on pathways of concealed and laundered money. We propose a method to identify and classify transactions and addresses of major mixing services in Bitcoin. Unlike previous research focusing on older techniques like CoinJoin, we emphasize modern mixing services. We gathered labelled data by transacting with three prominent mixers (MixTum, Blemder, and CryptoMixer) and identified recurring patterns. Using these patterns, an algorithm was created to pinpoint mixing transactions and distinguish mixerârelated addresses. The algorithm achieved a remarkable recall rate of 100%. Given the lack of clear ground truth and the vast number of unlabelled transactions, ensuring accuracy was a challenge. However, by analyzing a set of nonâmixing transactions with our model, it was confirmed that the high recall rate was not misleading. This work provides a significant advancement in monitoring mixing transactions, presenting a valuable tool against fraud and money laundering in cryptocurrency networks.
Jinho Choi, Taehwa LEE, Kwanwoo KIM, Min-Jae Seo ¡ 6 authors
Bitcoin is currently a hot issue worldwide, and it is expected to become a new legal tender that replaces the current currency started with El Salvador. Due to the nature of cryptocurrency, however, difficulties in tracking led to the arising of misuses and abuses. Consequently, the pain of innocent victims by exploiting these bitcoins abuse is also increasing. We propose a way to detect new signatures by applying two-fold NLP-based clustering techniques to text data of Bitcoin abuse reports received from actual victims. By clustering the reports of text data, we were able to cluster the message templates as the same campaigns. The new approach using the abuse massage template representing clustering as a signature for identifying abusers is much efficacious.
Criminals have become increasingly experienced in using cryptocurrencies, such as Bitcoin, for money laundering. The use of cryptocurrencies can hide criminal identities and transfer hundreds of millions of dollars of dirty funds through their criminal digital wallets. However, this is considered a paradox because cryptocurrencies are goldmines for open-source intelligence, giving law enforcement agencies more power when conducting forensic analyses. This paper proposed Inspection-L, a graph neural network (GNN) framework based on a self-supervised Deep Graph Infomax (DGI) and Graph Isomorphism Network (GIN), with supervised learning algorithms, namely Random Forest (RF), to detect illicit transactions for anti-money laundering (AML). To the best of our knowledge, our proposal is the first to apply self-supervised GNNs to the problem of AML in Bitcoin. The proposed method was evaluated on the Elliptic dataset and shows that our approach outperforms the state-of-the-art in terms of key classification metrics, which demonstrates the potential of self-supervised GNN in the detection of illicit cryptocurrency transactions.
Bitcoin is electronic money that uses a public protocol to implement it in a completely decentralized fashion, eliminating the need for it to be managed by a central issuing institution. It has been demonstrated to be a modern payment system that has been utilized in some procedures frequently connected with money laundering or the trafficking of illegal substances of various kinds, although it is still under development. As a result, in this essay, we examine the characteristics that turn a cryptocurrency into a valuable tool for conducting any type of transaction outside of the supervision of any regulatory agency, as well as some of the domains in which its use can lead to new illegal activities.
Manuel FebreroâBande, Wenceslao GonzĂĄlezâManteiga, Brenda Prallon, Yuri F. Saporito
This paper proposes a classification model for predicting the main activity of bitcoin addresses based on their balances. Since the balances are functions of time, we apply methods from functional data analysis; more specifically, the features of the proposed classification model are the functional principal components of the data. Classifying bitcoin addresses is a relevant problem for two main reasons: to understand the composition of the bitcoin market, and to identify addresses used for illicit activities. Although other bitcoin classifiers have been proposed, they focus primarily on network analysis rather than curve behavior. Our approach, on the other hand, does not require any network information for prediction. Furthermore, functional features have the advantage of being straightforward to build, unlike expert-built features. Results show improvement when combining functional features with scalar features, and similar accuracy for the models using those features separately, which points to the functional model being a good alternative when domain-specific knowledge is not available.
Abstract Online markets in cryptocurrency represent a sprawling and eclectic alternative financial system, selling cutting edge techno-investment schemes that are complex and high risk. Crime control is almost entirely absent from this new crypto economy, and it is full of scams. This paper draws on an ethnography of crypto trading to review the main types of scam, suggesting that the grey economy of cryptocurrency trading is part of a wider evolution of society towards the technosocial, and beyond that perhaps towards the metaversal.
Following the rampant increase in Bitcoin prices, there has been a proliferation of cryptocurrencies, which have become a major way of doing business across national boundaries. This paper investigates the link between cryptocurrency markets and drug trafficking activities. More specifically, we explore the impact of the announcement of 24 major drug busts on the systematic risk and return of the world cryptocurrency market. We deploy an event study methodology to estimate the abnormal returns associated with drug trafficking activities in the cryptocurrency market. We find that the relationship between the two is quite strong in the case of some cryptocurrencies, albeit weaker in others. However, we show that drug bust news tends to create uncertainty, and accordingly impart risk into cryptocurrency markets. This study confirms the predictions of convenience theories of crime as to the relative attractiveness of cryptocurrencies to criminals, and the extent to which not only general, but also their own future interests, sacrificed readily on the altar of accessibility. We highlight how when social and regulatory foundations are weak, criminal behaviour may overwhelm virtual spaces, marginalizing more orthodox businesses, no matter how altruistic the intentions of their founders.
The meteoric rise of Decentralized Finance (DeFi) has been accompanied by a plethora of frequent and often financially devastating attacks on its protocols There have been over 70 exploits of DeFi protocols, with the total of lost funds amounting to approximately 1.5bn USD. In this paper, we introduce a new approach to minimizing the frequency and severity of such attacks: dissimilar redundancy for smart contracts. In a nutshell, the idea is to implement a program logic more than once, ideally using different programming languages. Then, for each implementation, the results should match before allowing the state of the blockchain to change. This is inspired by and has clear parallels to the field of avionics, where on account of the safety-critical environment, flight control systems typically feature multiple redundant implementations. We argue that the high financial stakes in DeFi protocols merit a conceptually similar approach, and we provide a novel algorithm for implementing dissimilar redundancy for smart contracts.