Cryptocurrency Transactions Research Articles

Cryptocurrencies on the Tech Wave The Rise of Another Official Currency or Just a Dystopian Investment

Cryptocurrencies are a new form of currency that have gained widespread attention in today's age of rapid technological advancement. The underlying blockchain technology provides many advantages for cryptocurrency transactions, including decentralization, anonymity, and security. But there are always two sides to a story, and despite the fact that cryptocurrencies have solid technical backing, their development has been severely hampered by issues like the high stability of individual coins and the potential dangers of the technology itself, which have led many nations to pass laws restricting cryptocurrency use. Taking a literature review method, this paper explores the features of cryptocurrencies, their potential for institutionalization as legal tender, and their primary effect on the economy. This paper concludes that the widespread adoption of cryptocurrencies as a viable alternative to fiat currencies is highly improbable in the foreseeable future.

BlockDetective: A GCN‐based student–teacher framework for blockchain anomaly detection

AbstractThe anonymous and tamper‐proof nature of the blockchain poses significant challenges in auditing and regulating the behaviour and data on the chain. Criminal activities and anomalies are frequently changing, and fraudsters are devising new ways to evade detection. Moreover, the high volume and complexity of transactions and asymmetric errors make data classification more challenging. Also, class imbalances and high labelling costs are hindering the development of effective algorithms. In response to these issues, the authors present BlockDetective, a novel framework based on GCN that utilizes student–teacher architecture to detect fraudulent cryptocurrency transactions that are related to money laundering. The authors’ method leverages pre‐training and fine‐tuning, allowing the pre‐trained model (teacher) to adapt better to the new data distribution and enhance the prediction performance while teaching a new, light‐weight model (student) that provides abstract and top‐level information. The authors’ experimental results show that BlockDetective outperforms state‐of‐the‐art research methods by achieving top‐notch performance in detecting fraudulent transactions on the blockchain. This framework can assist regulators and auditors in detecting and preventing fraudulent activities on the blockchain, thereby promoting a more secure and transparent financial system.

Developments in Cryptocurrency Transactions and Implications for Audit and Accounting Activities

Developments in Cryptocurrency Transactions and Implications for Audit and Accounting Activities

The regulation of cryptocurrencies to combat money laundering crimes in South African banking institutions

Cryptocurrencies have become an increasingly popular means of conducting financial transactions globally, and South African banking institutions have not been immune to this trend. However, the pseudonymous nature of cryptocurrency transactions has made it an attractive tool for money laundering activities. In response, there is a growing need for South African regulators to establish a legal framework to regulate the use of cryptocurrency to combat money laundering crimes by banking institutions. While the recent amendments to the Financial Intelligence Centre Act 38 of 2001 (as amended) regarding cryptocurrencies are commendable, it is not without deficiencies. The purpose of this article is threefold. First, it examines the current state of cryptocurrency regulation in South Africa. Second, it explores the vulnerabilities that expose the banking system to money laundering using cryptocurrencies. Third, it highlights the need for further development and implementation of regulatory measures to address vulnerabilities identified in this article. This article argues that the current lack of a comprehensive regulatory framework for cryptocurrencies in South Africa leaves the banking system open to potential abuse. The article suggests that South African regulators should focus on three key areas to combat money laundering activities related to cryptocurrency. First, regulatory measures should be implemented to identify and verify the identities of cryptocurrency traders and investors. Second, measures should be put in place to monitor the flow of cryptocurrency transactions and detect suspicious activities. Third, the digital wallets of crypto users should be managed by South African banking institutions.

Problems With Digital Currency: Cryptocurrency In Indonesia

This study aims to analyze the Indonesian government's policies regarding cryptocurrency transactions and taxation and accounting practices in Indonesia. In addition, this research also conducts literature studies abroad. Commodity Futures Trading Regulatory Agency Regulation No. 13 of 2022 and No. 8 of 2021 concern guidelines for organizing crypto asset physical market trading on futures exchanges to oversee cryptocurrency transactions. Cryptocurrency transactions in Indonesia are considered VAT objects and are subject to income tax. Accountants face a challenge because there is no accounting standard that explains why cryptocurrency must be considered. It is hoped that the Indonesian Accounting Standards Board can conduct discussions related to accounting standards for cryptocurrency. Besides, the government's role is very important in making financial technology policies and systems in order to mitigate the risks of cryptocurrency transactions so that they can benefit investors and the tax system in Indonesia.

Tax on income obtained from cryptocurrency transactions

The following research is aimed at individuals tangentially involved with digital or virtual currencies, who are increasingly facing questions about how to declare income derived from trading these financial instruments. The purpose of the research is to present the tax treatment of transactions with cryptocurrencies in the part related to the taxation of the income of legal entities and individuals obtained from the activity of trading with virtual currencies according to the legislation of the Republic of Moldova, as well as the practice followed in other countries. The issue of taxation of these types of income is a current one both at the level of the legislation of the Republic of Moldova and at an international level, given the fact of abundant flooding of the world economy with an enormously large number of cryptocurrencies without which today the financial-banking system would look like a quaint one. It is worth mentioning that the clarity of the tax legislation regarding the taxation of new types of income, or the synchronous advancement of the tax legislation with the up-to-date needs of the taxpayers is a priority both for the institutions that collect the sources of the state budget, as well as the income payers. In other words, increasing the clarity of the tax legislation and the tendency to align with international standards and practices ensure greater efficiency in the successful administration of state revenues and an upward growth in the number of compliant taxpayers. At the same time, this research aims to examine the causal link between the harmonization of legislation to the needs of the market with the level of compliance of taxpayers and receipts to the state budget. The scientific methods used in the study are as follows: analysis of the legal framework governing the research, synthesis of information, comparison to identify distinctive features, deduction of challenges.

Detecting anomalous cryptocurrency transactions: An AML/CFT application of machine learning-based forensics

In shaping the Internet of Money, the application of blockchain and distributed ledger technologies (DLTs) to the financial sector triggered regulatory concerns. Notably, while the user anonymity enabled in this field may safeguard privacy and data protection, the lack of identifiability hinders accountability and challenges the fight against money laundering and the financing of terrorism and proliferation (AML/CFT). As law enforcement agencies and the private sector apply forensics to track crypto transfers across ecosystems that are socio-technical in nature, this paper focuses on the growing relevance of these techniques in a domain where their deployment impacts the traits and evolution of the sphere. In particular, this work offers contextualized insights into the application of methods of machine learning and transaction graph analysis. Namely, it analyzes a real-world dataset of Bitcoin transactions represented as a directed graph network through various techniques. The modeling of blockchain transactions as a complex network suggests that the use of graph-based data analysis methods can help classify transactions and identify illicit ones. Indeed, this work shows that the neural network types known as Graph Convolutional Networks (GCN) and Graph Attention Networks (GAT) are a promising AML/CFT solution. Notably, in this scenario GCN outperform other classic approaches and GAT are applied for the first time to detect anomalies in Bitcoin. Ultimately, the paper upholds the value of public–private synergies to devise forensic strategies conscious of the spirit of explainability and data openness.

Understanding the Legal and Religious Perspectives on Cryptocurrency Transactions: A Study of DSN - MUI Fatwa and Indonesian Currency Regulation

A growing economy creates cryptocurrency virtual money residing in cyberspace. Cryptocurrency Is an online payment tool that uses an open source peer-to-peer payment network. There are many problems faced by users, where Cryptocurrencies are said to include money or a commodity. This phenomenon really makes users feel uncomfortable, feel at a loss, therefore the government must immediately provide an evaluation of the use of Cryptocurrency as a means of obtaining transactions. more attention, especially from the government so that the community gets their rights and obligations in muamalah. This paper aims to discuss how to use Cryptocurrency transactions from the Perspective of the DSN-MUI Fatwa and Law No. 7 of 2011. This research is classified as normative research, using a statutory approach and a conceptual approach. The results of the discussion show that Cryptocurrency is linked in the DSN MUI fatwa No.28/DSN-MUI/III/2002 regarding al-sharf that in the provisions of the fatwa the conditions for exchanging Cryptocurrency digital money are prohibited because of the element of speculation. In Article 2 paragraph (1) of Law Number 7 of 2011 concerning Cryptocurrency, it does not meet the requirements as a type of currency in Indonesia. Judging from the six criteria of money, Cryptocurrency only meets the criteria of portability and visibility.

Batching of Tasks by Users of Pseudonymous Forums: Anonymity Compromise and Protection

In a number of applications where anonymity is critical, users act under pseudonyms to preserve their privacy. For instance, in scientific peer review using forums like OpenReview.net, reviewers make comments on papers that are publicly viewable. Reviewers who have been assigned multiple papers operate under different pseudonyms across their papers to remain anonymous. Other examples of publicly visible tasks where users operate under pseudonyms include Wikipedia editing and cryptocurrency transactions. In these settings, it is common for users to engage in batching - the completion of several similar tasks at the same time. Batching occurs both due to natural bursts in activity (e.g., a person visits a website and makes many comments at once) or as a productivity strategy used to streamline work. In peer-review forums such as computer science conferences, reviewers and meta-reviewers are often assigned multiple papers. We find empirically that reviewers are highly likely to batch their comments and/or reviews across papers. In analysis of data from a top Computer Science conference with thousands of papers, reviewers, and discussion comments we find that when reviewers and meta-reviewers comment on multiple papers, they have a 30.10% chance of batching their comments within 5 minutes of one other. In comparison, any randomly chosen pair of reviewers and meta- reviewers had only a 0.66% chance of making comments on different papers within 5 minutes of each other.

Macroeconomic news and intraday seasonal volatility in the cryptocurrency markets

ABSTRACT We examine the effects of US, German, and Japanese macroeconomic news surprises and monetary policy decisions on the intraday cyclical volatility of Bitcoin and Ethereum markets. We first document intraday seasonality specific to each day of the week and show that these patterns exhibit a slightly different volatility compared to all-day seasonality. Second, the US monetary policy news and macroeconomic surprises generate the largest effect on the seasonal volatility. Third, Ethereum seasonality is more sensitive to macroeconomic fundamentals compared to Bitcoin. These results suggest that to improve cryptocurrency pricing, portfolio management, and risk management practices associated with cryptocurrency transactions, investors should consider the interactions between day of the week effects, intraday seasonality patterns and the macroeconomics news releases.

Could Cryptocurrency Policy Uncertainty Facilitate U.S. Carbon Neutrality?

Investigating the essential impact of the cryptocurrency market on carbon emissions is significant for the U.S. to realize carbon neutrality. This exploration employs low-frequency vector auto-regression (LF-VAR) and mixed-frequency VAR (MF-VAR) models to capture the complicated interrelationship between cryptocurrency policy uncertainty (CPU) and carbon emission (CE) and to answer the question of whether cryptocurrency policy uncertainty could facilitate U.S. carbon neutrality. By comparison, the MF-VAR model possesses a higher explanatory power than the LF-VAR model; the former’s impulse response indicates a negative CPU effect on CE, suggesting that cryptocurrency policy uncertainty is a promoter for the U.S. to realize the goal of carbon neutrality. In turn, CE positively impacts CPU, revealing that mass carbon emissions would raise public and national concerns about the environmental damages caused by cryptocurrency transactions and mining. Furthermore, CPU also has a mediation effect on CE; that is, CPU could affect CE through the oil price (OP). In the context of a more uncertain cryptocurrency market, valuable insights for the U.S. could be offered to realize carbon neutrality by reducing the traditional energy consumption and carbon emissions of cryptocurrency trading and mining.

QQ Payment Gateway: A Comprehensive Solution for Small Businesses to Seamlessly Integrate Fiat and Cryptocurrency Transactions

QQ Payment Gateway: A Comprehensive Solution for Small Businesses to Seamlessly Integrate Fiat and Cryptocurrency Transactions

Fintech and the Digital Transformation of Financial Services

By creating a decision-making mechanism that relies on data as the basis for decisions, fintech is accelerating the change in the financial sector. The financial markets have faced numerous possibilities and problems as a result of their continuing rise. Fintech is a broad term that can refer to anything from straightforward mobile payment apps to intricate blockchain networks that process cryptocurrency transactions. This paper reviews the literature on the continuous development of fintech and investigates how it is altering financial markets by gathering pertinent data for in-depth study. It has been discovered that fintech is a two-edged sword for the financial markets. Many sectors now have access to comprehensive and up-to-date decision support information as a result of its development and utilization. But at the same time, traditional financial services are replaced by new technologies such as the Internet, and the complexity and risk brought about by fintech will also manifest itself.

Pengaruh Pemungutan Pajak atas Transaksi Cryptocurrency dan Literasi Keuangan terhadap Niat Berinvestasi pada Cryptocurrency

The transformation of information technology gave birth to the latest innovations, one example of which is public access to the financial transaction sector. The purpose of this study is to determine the effect of tax collection on cryptocurrency transactions and financial literacy on the intention to invest in cryptocurrency. This research uses a type of research using quantitative methods whose data uses statistical analysis and uses numbering. The population used in this study is all millennial generation in the istmewa area of Yogyakarta. The sample used for this study was a millennial generation with an age range of 18-50 years totaling 114 people. Sample collection technique with snowball sampling model where the distribution of questionnaires to resonence is carried out online, how to distribute questionnaires using social media (WhatsApp, Twitter, and Instagram). The study used multiple linear regression analysis. In the research that has been done, it can be concluded that tax collection on cryptocurrency transactions does not have an influence on investment intentions. Financial literacy has a positive influence on the intention to invest in cryptocurrencies. The results of research and discussion of each variable illustrate that financial literacy has an influence on the intention to invest in cryptocurrency for respondents, most of whom are students. This proves that financial literacy such as understanding and skills in managing finances have been applied well by students when deciding to invest.

Detection of Illegal Transactions of Cryptocurrency Based on Mutual Information

In recent times, there has been a swift advancement in the field of cryptocurrency. The advent of cryptocurrency has provided us with convenience and prosperity, but has also given rise to certain illicit and unlawful activities. Unlike classical currency, cryptocurrency conceals the activities of criminals and exposes their behavioral patterns, allowing us to determine whether present cryptocurrency transactions are legitimate by analyzing their behavioral patterns. There are two issues to consider when determining whether cryptocurrency transactions are legitimate. One is that most cryptocurrency transactions comply with laws and regulations, but only a small portion of them are used for illegal activities, which is related to the sample imbalance problem. The other issue concerns the excessive volume of data, and there are some unknown illegal transactions, so the data set contains an abundance of unlabeled data. As a result, it is critical to accurately distinguish between which transactions among the plethora of cryptocurrency transactions are legitimate and which are illegal. This presents quite a difficult challenge. Consequently, this paper combines mutual information and self-supervised learning to create a self-supervised model on the basis of mutual information that is used to improve the massive amount of untagged data that exist in the data set. Simultaneously, by merging the conventional cross-entropy loss function with mutual information, a novel loss function is created. It is employed to address the issue of sample imbalance in data sets. The F1-Score results obtained from our experimentation demonstrate that the novel loss function in the GCN method improves the performance of cryptocurrency illegal behavior detection by four points compared with the traditional loss function of cross-entropy; use of the self-supervised network that relies on mutual information improves the performance by three points compared with the original GCN method; using both together improves the performance by six points.

Follow the Money: Analyzing Darknet Activity Using Cryptocurrency and the Bitcoin Blockchain

Transactions on the darknet are notoriously difficult to examine. Prior criminological research has generally used web scraping and qualitative text analysis to examine illegal darknet markets. One disadvantage of this process is that individuals can lie. Fortunately for researchers, the currency used for transactions on the darknet, cryptocurrency, is designed to be tracked. In this article, we examine transactions from a former darknet marketplace, AlphaBay. Using the blockchain, we examine the interconnectedness of both legal and illegal cryptocurrencies. In addition, we provide a structured approach to quantitatively examine the Bitcoin blockchain ledger, offering both the tools and our own experiences for other researchers interested in such approaches. While cybersecurity, information technology, accounting, and other disciplines can examine the financial data itself, we believe that criminologists can provide additional benefits in pattern analysis and organizing the context and theory around the transactions. Our results show that cryptocurrency transactions are generally identifiable (90%) and involve likely illegal transactions, transactions that attempt to obfuscate other transactions, and legal transactions. We end with a discussion of newer cryptocurrencies and related technology and how they will likely shape future work.

NimbleChain: Speeding up Cryptocurrencies in General-purpose Permissionless Blockchains

Nakamoto’s seminal work gave rise to permissionless blockchains, as well as a wide range of proposals to mitigate their performance shortcomings. Despite substantial throughput and energy efficiency achievements, most proposals only bring modest (or marginal) gains in transaction commit latency. Consequently, commit latencies in today’s permissionless blockchain landscape remain prohibitively high. This article proposes NimbleChain, a novel algorithm that extends permissionless blockchains based on Nakamoto consensus with a fast path that delivers causal promises of commitment or simply promises . Since promises only partially order transactions, their latency is only a small fraction of the totally ordered commitment latency of Nakamoto consensus. Still, the weak consistency guarantees of promises are strong enough to correctly implement cryptocurrencies. To the best of our knowledge, NimbleChain is the first system to bring together fast, partially ordered transactions with consensus-based, totally ordered transactions in a permissionless setting. This hybrid consistency model is able to speed up cryptocurrency transactions while still supporting smart contracts, which typically have (strong) sequential consistency needs. We implement NimbleChain as an extension of Ethereum and evaluate it in a 500-node geo-distributed deployment. The results show NimbleChain can promise a cryptocurrency transactions up to an order of magnitude faster than a vanilla Ethereum implementation, with marginal overheads.

How Should We Regulate Cryptocurrencies via Consensus?: A Strategic Framework for Optimal Legal Transaction Throughput

Permissionless blockchain consensus protocols have been leveraged for defining decentralized economies for the (commercial or private) trade of virtual and physical assets, using cryptocurrencies. In most instances, the assets being traded are regulated , which mandates that the legal right to their trade and their trade value are determined by the governmental regulator of the jurisdiction in which the trade occurs. Unfortunately, existing blockchains do not formalize proposal of legal cryptocurrency transactions, as part of the execution of their respective consensus protocols, resulting in illegal activities in the associated crypto-economies. In this contribution, unlike existing non-consensus solutions, which are prone to be more compute-time and audit-time intensive, we present a novel regulatory framework for blockchain protocols, for ensuring legal transaction confirmation as part of the blockchain consensus. As per our regulatory framework, we derive, through a stochastic game analysis, block proposal strategies under which legal transaction throughput supersedes throughput of traditional transactions, which are, in the worst case, an indifferentiable mix of legal and illegal transactions. Finally, we show that when a majority of the consensus protocol participants are licensed by the regulator to propose legal transactions, there exists a fair consensus execution policy to maximize the legal transaction throughput in the blockchain network.

Inspection-L: self-supervised GNN node embeddings for money laundering detection in bitcoin

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 proposes 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.

CRYPTOCURRENCY MARKET TRANSFORMATION DURING PANDEMIC COVID-19

The pandemic and subsequent changes in various spheres of human activity have also transformed consumer behavior, particularly in the cryptocurrency market. The article is aimed at identifying the priority directions of transformations taking place in the cryptocurrency market in the conditions of the Covid-19 pandemic under the influence of certain groups of factors. System and network approaches to understanding the cryptocurrency market have been identified. The cryptocurrency market is considered from a functional and institutional point of view. From a functional point of view, the cryptocurrency market is a set of economic relations in cyberspace regarding cryptocurrency mining, initial coin offering (ICO) and circulation of cryptocurrencies based on the laws of supply and demand. From an institutional point of view, the cryptocurrency market is a set of participants in the virtual currency schemes who carry out cryptocurrency transactions. The following signs of cryptocurrency market segmentation are justified such as those depending on the market capitalization of the cryptocurrency; on the nature of the crypto assets movement; on operations carried out on the market; on the region; on consumers of services. Factors which influence the functioning of the cryptocurrency market are systematized according to the following groups: macroeconomic, price, environmental, geographic, market, behavioral and technological. The influence of gold, oil prices, the daily number of Covid-19 cases and deaths from Covid-19, the MSCI ACWI global stock index, the iShares MSCI All Country Asia ex Japan ETF, the Wilshire 5000 Total Market Index on the Bitcoin exchange rate is revealed. The trends in the cryptocurrency market development in the post-war period are justified, namely the growth of investors’ interest in cryptocurrencies against the background of the initial coin offering collapse; growth of payments in cryptocurrencies; strengthening the regulatory landscape on a global and national scale; integration of the cryptocurrency market with traditional finance; attracting non-typical participants to the cryptocurrency business; expansion of participants in the infrastructure of the cryptocurrency market due to the rapid cryptocurrency market development, in particular, due to the production of equipment for its operation.