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893 results · page 12 of 38
Grace Akhihiero
No abstract is available for this record.
Ishaq Asly, Driss Essabbar
The adoption of emerging technologies in the finance industry, such as blockchain, promises to provide new perspectives on data security and business processes. This advanced innovation paves the way for unprecedented financial and organizational optimization, transforming not only processes and structures, but also fundamental paradigms of trust and knowledge. The financial industry faces numerous challenges in combating fraud and embezzlement, due to the complexity and scale of its operations. Therefore, the infrastructure provided by the blockchain system helps reduce costs related to intermediaries, enhances security, and improves trust between stakeholders, thanks to the principle of decentralization and the immutability of its ledger. Furthermore, this technological revolution offers financial actors the ability to create new services and solutions in order to meet the needs of several business activities, especially those with complex supply chains. A perfect use of it, will certainly develop the standards of this industry and stimulate innovative economic growth. Although the blockchain offers substantial opportunities for the financial sector, its potential can only be fully achieved with adequate regulatory support, as a way to steer the system toward a more digital and inclusive economy. After a presentation of blockchain technology and its mode of operation, we will be focusing on its potential in finance and how it might provide creative accounting and financial management solutions.
David Krause
No abstract is available for this record.
Cayetana Santaolalla
No abstract is available for this record.
Thong Li Yi, Ricky Chia Chee Jiun, Mohd Fahmi Ghazali
Among all the cryptocurrencies in the market, Bitcoin is the most widely discussed and most popular cryptocurrency in the cryptocurrency market. This study aims to review and summarize the existing literature findings pertaining to the impact of geopolitical risk and economic policy uncertainty on Bitcoin. The results shown geopolitical risk and economic policy uncertainty have predictive power on Bitcoin prices. Both economic policy uncertainty and geopolitical risk have positive and negative effects on Bitcoin. The geopolitical risk and economic policy uncertainty able serve as a hedging instrument against Bitcoin. Bitcoin also can act as a safe haven against geopolitical risk and economic policy uncertainty. A summary of further implication from previous study suggested utilizing other uncertainty measures, applying other cryptocurrency, exploring Bitcoin’s relationship with other financial assets, and employing alternative methodologies.
Milad Keshvari Fard, Jingshu Liu
The transformative power of blockchain and cryptocurrencies has rippled across diverse industries, sparking innovation and redefining established norms. In this chapter, we explore how the nonprofit sector can tap into the vast potentials of cryptocurrencies in fundraising, providing financial inclusion to disadvantaged population, and helping the underdeveloped communities. Furthermore, we examine the challenges associated with adopting cryptocurrencies, as well as strategies to navigate and harness these challenges effectively.
Bekti Cahyo Hidayanto, Izzat Aulia Akbar, R. Aditya Rayhan Zanesty
This study focuses on specifically looking at how penetration testing affects the market value of smart contracts. This study uses a web-based IDE to deploy smart contracts, and it performs penetration testing utilizing reentrancy and delegatecall attacks. The targeted smart contract is exposed to potential exploitation as a result of the assaults' successful implementation. This study shows that penetration testing indirectly affects token prices since incorrect parameter selection and successful attacks might cause changes in token prices. The results emphasize how critical it is to find and fix smart contract vulnerabilities in order to reduce risks and potential losses.
Daehan Kim, Jing Chen, Doojin Ryu, Robert I. Webb
No abstract is available for this record.
Juan Ignacio Ibañez, Aayush Ladda, Paolo Tasca, Logan Aldred
The environmental impact of Bitcoin mining has become a significant concern, prompting several governments to consider or implement bans on cryptocurrency mining. However, these well-intentioned policies may lead to unintended consequences, notably the redirection of mining activities to regions with higher carbon intensities. This study aims to quantify the environmental effectiveness of Bitcoin mining bans by estimating the resultant carbon emissions from displaced mining operations. Our findings indicate that, contrary to policy goals, Bitcoin mining bans in low-emission countries can result in a net increase in global carbon emissions, a form of aggravated carbon leakage. We further explore the policy implications of these results, suggesting that more nuanced approaches may be required to mitigate the environmental impact of cryptocurrency mining effectively. This research contributes to the broader discourse on sustainable cryptocurrency regulation and provides a data-driven foundation for evaluating the true environmental costs of Bitcoin regulatory policies.
Husan S. UMAROV
The prospects for the widespread introduction of decentralized finance into global financial markets are analyzed. The aim of the study is to consider the opportunities provided to users and investors by the DeFi ecosystem (decentralized finance), and the potential risks of implementing services, applications, protocols based on decentralized financial instruments in both foreign and Russian financial markets. With the help of the theoretical (analysis, synthesis, abstraction) and empirical (comparison, observation) research methods, opinions of leading domestic and foreign experts on the innovative capabilities of DeFi are presented. Based on up-to-date statistical data from the innovative dApps – DappRadar platform, analytical reviews, conference reports, public speeches and expert interviews, initiatives of the main financial regulator of the United States – The United States Securities and Exchange Commission (The United States Securities and Exchange Commission), the Commodity Futures Trading Commission (CFTC), and the Russian Financial Action Task Force (FATF) group for the development of financial measures to combat money laundering, the author emphasizes the need to implement a regulatory framework to settle the spread of decentralized finance. The resulting conclusions are the inclusion of digital assets in the “anti-money laundering” legislation of Russia, as well as a number of other measures aimed at bringing regulatory clarity to the sphere of DeFi initiatives. The main conclusion of the study highlights the difficulties in the large-scale spread of decentralized finance, which is justified by the direct impact of potential risks of using it, distributed by the author to a number of system groups. As a promising predictive model for the development of DeFi, the author proposes a safe harbor model for tokens developed by Hester Peirce. The relevance and scientific novelty of the research are justified by the possibility of using the achieved results (including in the field of analyzing initiatives recommended by large regulatory institutions in relation to uncontrolled financial markets) to introduce a transparent, open, reliable ecosystem of decentralized finance.
Ariel Burgess, Rhianna Hamilton, Christian Leuprecht
Abstract Inadequate oversight and an inchoate appreciation are giving terrorist groups ready access to transboundary financial transfers by means of virtual currency. This chapter counters the prevailing approach that treats cryptocurrency-enabled crimes, such as terrorism, as monolithic. This chapter demonstrates that terrorist groups are using cryptocurrency and decentralized finance to fundraise and transfer funds in conjunction with the traditional financial system. Since actual case studies are few and data limited, this chapter is a proof of concept: it compares terrorist financing schemes by the Al-Qassam Brigades and Al Qaeda that used virtual assets. The comparison of virtual assets being used finds that standards developed and recommended by the Financial Action Task Force (FATF) are wholly inadequate to contain the proliferation of decentralized finance technology and centralized virtual assets as drivers of the global Illicit International Political Economy (IIPE). FATF recommendations are not sufficiently nuanced, nor are they effective at detecting, disrupting and deterring he nexus of crypto, crime and terror. To make matters worse, FATF members are falling short on implementing even FATF’s inadequate standards. The chapter concludes that FATF needs to: clarify inclusion criteria under the current definition of virtual assets; broaden regulations, improve interagency collaboration, and formulate more nuanced recommendations that are sensitive to crypto-enabled crimes across different criminal activities and criminogenic factors.
Zulfiqar Ali Khan, Akbar Siami Namin
Smart Contracts (SCs) communicate with each other using external calls. Their interactions can be malicious, resulting in the loss of Ether. One can blame the reentrancy attack for this exploitation. Several previous endeavors detected the reentrancy vulnerability by creating testing tools using static analysis like Remix. However, these approaches do not execute the programs; hence, we cannot confirm their results. In this paper, we present TechyTech that detects both reentrancy and tx.origin vulnerabilities using a novel dynamic analysis approach of involuntary transfer (i.e., unintended transfer). Henceforth, we use a tree-based categorization string to distinguish the two vulnerabilities and their variations. Further, our research discusses multiple SC-related issues like the hijacked stack, deployed owner, and non-generation of transaction receipts in connection with reentrant calls, which we could not find in previous work. Using an example, we demonstrate how the actual Ether transfer is greater than the intended due to reentrancy.We acknowledge that due to dynamic analysis, TechyTech may suffer from VMExceptions.
Alesia Zhuk
This article explores the evolution of crypto-anarchy, tracing its origins from the cypherpunk movement to the rise of decentralized finance (DeFi) and its transformative effects on legal and economic systems. Central to crypto-anarchy is the belief in individual empowerment through privacy, financial autonomy, and decentralization, which allows users to bypass traditional intermediaries like banks. While these technologies offer increased freedom and financial inclusion, they also introduce significant risks such as money laundering, tax evasion, and the facilitation of illegal activities, posing challenges to current regulatory frameworks. The article examines the socio-economic implications of decentralization, including both the democratization of finance and the widening wealth disparities, as early adopters often gain disproportionate rewards. Environmental concerns related to energy-intensive cryptocurrencies like Bitcoin and ethical dilemmas surrounding privacy versus accountability are also addressed. The article concludes by examining the potential for AI, blockchain, and decentralized governance models to further disrupt traditional financial and governance structures, while emphasizing the need for robust regulatory frameworks to mitigate risks and ensure long-term sustainability. It envisions a future where decentralized technologies contribute to a more transparent, equitable, and participatory global economy.
Jiajing Wu, Yunmei Yu, Lin Dan, Zhe Chen · 5 authors
No abstract is available for this record.
Ferda Özdemir Sönmez, William J. Knottenbelt
This paper presents an ongoing study of a novel attack surface generator tool for smart contracts developed in Solidity. The tool leverages a rule-based engine and ChatGPT API for security analysis. The rule-based engine provides numerical values and key variables and functions for further analysis, while ChatGPT handles complex queries. However, ChatGPT may generate similar responses for more general questions, irrespective of the given contract code. The tool combines both approaches to identify and mitigate potential security vulnerabilities in Solidity-based smart contracts. The effectiveness of the tool is evaluated on real-world smart contracts, and its potential for detecting and preventing common attack vectors is demonstrated.
Hakan Yilmazkuday
Abstract This study examines how global geopolitical risks , threats , and acts impact the daily returns of 10 major cryptocurrencies (BTC, ETH, USDT, XRP, BNB, USDC, BCH, DOGE, LTC, and ADA). The statistically significant results that are robust to the consideration of alternative model specifications and control variables suggest that there is strong evidence for (i) ETH, XRP, BNB and BCH responding negatively to the shocks of geopolitical risks , (ii) BTC, ETH, BNB, BCH, LTC and ADA responding negatively to the shocks of geopolitical threats , and (iii) all 10 cryptocurrencies not responding to the shocks of geopolitical acts . As these 10 cryptocurrencies do not respond positively to any of the three shocks in a robust and statistically significant way either, it is implied that none of them offer a reliable hedge against geopolitical risks.
Lee Song Haw Colin, P. Mohan, Jonathan Pan, Peter K. K. Loh
Smart contract vulnerabilities have led to substantial disruptions, ranging from the DAO attack to the recent Poolz Finance. While initially, the smart contract vulnerability definition lacked standardization, even with the advancements in Solidity, the potential for deploying malicious contracts to exploit legitimate ones persists. The Abstract syntax tree (AST), opcodes, and control flow graph (CFG) are the intermediate representations for Solidity contracts. In this paper, we propose an integrated and efficient smart contract vulnerability detection algorithm based on Multi-layer perceptron (MLP). We use feature vectors from the Opcodes and CFG for the machine learning (ML) model training. The existing ML-based approaches for analyzing the smart contract code are constrained by the vulnerability detection space, significantly varying Solidity versions, and no unified approach to verify against the ground truth. The primary contributions in this paper are (i) a standardized pre-processing method for smart contract training data, (ii) introducing bugs to create a balanced dataset of flawed files across Solidity versions using AST, and (iii) standardizing vulnerability identification using the Smart Contract Weakness Classification (SWC) registry. The ML models employed for benchmarking the proposed MLP, and a multi-input model combining MLP and Long short-term memory (LSTM) in our study are Random forest (RF), XGBoost (XGB), Support vector machine (SVM). The performance evaluation onreal-timesmart contracts deployed on the Ethereum Blockchain show an accuracy of up to 91% using MLP with the lowest average False Positive Rate (FPR) among all tools and models, measuring at 0.0125.
Mohammad Mustafa Ibrahimy, Alex Norta, Peeter Normak
Corruption and lack of transparency remain critical challenges in governance systems around the world. These issues are often perpetuated by centralized systems and their manipulation by system administrators. Furthermore, the lack of data ownership and the monetization of user data by tech companies further increase concerns about transparency. In light of these concerns, this study aims to review existing blockchain-based governance models and identify best-practice governance models focusing on corruption transparency, their characteristics, and components. The research will also examine the role of a token economy in addressing trusted third-party issues related to asset ownership management. Furthermore, we discuss the effect of smart contracts, blockchain, decentralized autonomous organizations (DAO), Web 3.0, and multifactor challenge set self-sovereign identity authentication (MFSSIA) as modern technologies to combat corruption and achieve transparency in the public sector. To achieve this, we conduct a systematic literature review (SLR) comprising peer-reviewed journals, proceedings, and book chapters published between 2012 and 2023. Using the SLR methodology, 45 primary and supporting studies have been selected for result extraction and analysis. Finally, we discovered seven blockchain-based governance models with their characteristics and primary components.
Ismail Alarab, Simant Prakoonwit
Abstract Money laundering has urged the need for machine learning algorithms for combating illicit services in the blockchain of cryptocurrencies due to its increasing complexity. Recent studies have revealed promising results using supervised learning methods in classifying illicit Bitcoin transactions of Elliptic data, one of the largest labelled data of Bitcoin transaction graphs. Nonetheless, all learning algorithms have failed to capture the dark market shutdown event that occurred in this data using its original features. This paper proposes a novel method named recurrent graph neural network model that extracts the temporal and graph topology of Bitcoin data to perform node classification as licit/illicit transactions. The proposed model performs sequential predictions that rely on recent labelled transactions designated by antecedent neighbouring features. Our main finding is that the proposed model against various models on Elliptic data has achieved state-of-the-art with accuracy and $$f_1$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:msub> <mml:mi>f</mml:mi> <mml:mn>1</mml:mn> </mml:msub> </mml:math> -score of 98.99% and 91.75%, respectively. Moreover, we visualise a snapshot of a Bitcoin transaction graph of Elliptic data to perform a case study using a backward reasoning process. The latter highlights the effectiveness of the proposed model from the explainability perspective. Sequential prediction leverages the dynamicity of the graph network in Elliptic data.
Sergio Luis Náñez Alonso, Miguel Ángel Echarte Fernández, David Sanz Bas, Cristina Pérez Pérez
ABSTRACT The objective of this article is to analyze the two most important monetary laws that have been implemented in El Salvador, namely the Monetary Integration Law (MIL) and the Bitcoin Law. The most important articles of both laws will be analyzed, as well as the consequences of dollarization, and the possible advantages and risks associated with the adoption of Bitcoin as legal tender. Although this measure may have some positive aspects by encouraging financial innovation and facilitating remittances, the macroeconomic risk is very high due to the volatility of this cryptocurrency. So far no positive results have been achieved as the acceptance has been very low and there has been a depreciation of the asset in recent months.
Hou-Wan Long, Xiongfei Zhao, Yain‐Whar Si
Decentralized Finance (DeFi), propelled by Blockchain technology, has revolutionized traditional financial systems, improving transparency, reducing costs, and fostering financial inclusion. However, transaction activities i n these systems fluctuate significantly and the throughput can be effected. To address this issue, we propose a Dynamic Mining Interval (DMI) mechanism that adjusts mining intervals in response to block size and trading volume to enhance the transaction throughput of Blockchain platforms. Besides, in the context of public Blockchains such as Bitcoin, Ethereum, and Litecoin, a shift towards transaction fees dominance over coin-based rewards is projected in near future. As a result, the ecosystem continues to face threats from deviant mining activities such as Undercutting Attacks, Selfish Mining, and Pool Hopping, among others. In recent years, Dynamic Transaction Storage (DTS) strategies were proposed to allocate transactions dynamically based on fees thereby stabilizing block incentives. However, DTS’ utilization of Merkle tree leaf nodes can reduce system throughput. To alleviate this problem, in this paper, we propose an approach for combining DMI and DTS. Besides, we also discuss the DMI selection mechanism for adjusting mining intervals based on various factors.
E. L. Sidorenko
Objective : to increase the effectiveness of countering the use of typical criminal money laundering schemes by identifying the technological and legal vulnerabilities of the DeFi infrastructure: decentralized exchanges, blockchain bridges, decentralized wallets, and privacy-enhanced currencies. Methods : general scientific (analysis and synthesis, induction and deduction, theoretical modeling, legal interpretation) and special methods of scientific cognition (structural-functional, constructive, situational, innovative, target-oriented, program-target, and risk-oriented). Results : the main trends in the development of money laundering using decentralized finance were outlined; the determinative significance of DeFi technological characteristics in the genesis of money laundering was revealed; the main types of money laundering using decentralized finance were identified; the schemes of committing crimes were studied and the criminogenic potential of DeFi infrastructure (decentralized exchanges, blockchain bridges, mixers, privacy-enhanced tokens, etc.) was assessed. Scientific novelty : it is proposed to consider money laundering using DeFi as a special type of digital financial crime. The article proposes the author’s typology of money laundering, substantiates the idea that the matrix of traditional financial regulation and AML standards cannot be applied to decentralized finance. It is argued that prevention of money laundering using decentralized finance should be carried out in close connection with the identification of risk indicators and the development of effective control measures at the points of entry of criminal incomes to centralized exchanges. Practical significance : the analysis of typical mechanisms of money laundering using DeFi allows a systematic approach to the organization of early crime prevention and can potentially become the basis to develop recommendations for financial intelligence and monitoring services.
Alper Uyumaz, Enku Tensay Woldemaryam
Abstract The article analyses the current issues contributing to the volatility of Bitcoin as the reliability of this new technology diminishes, leading to increased unpredictability of its value. Legal efforts and literature regarding Bitcoin have primarily focused on protecting society from the illegal use of this digital technology, with little emphasis on integrating it as an asset. However, this article proposes that countries adopt Bitcoin-related legislation, incorporating recognition and regulation clauses to transform Bitcoin into a stable, less volatile and functional digital asset. In the context of legal history, primary legal domains, such as contracts, family, trade and others, have been integrated through recognition and regulation processes. Therefore, we argue that adopting Bitcoin-specific legislation that recognizes this new technology while comprehensively regulating the associated risks would enhance the coin's stability and reduce volatility, ultimately increasing trust among digital investors and users.
Anatolii Movchan, Oleksandr Shliakhovskyi, Vasyl Kozii, Ihor Fedchak
The article is devoted to the study of the problems of investigating crimes of financing terrorism and armed aggression with cryptocurrency, which is relevant considering the attack on Ukraine by the Russian Federation, as well as in connection with the significant spread and use of cryptocurrency for financing both terrorism and armed aggression. The purpose of the article is to study the problems of investigating crimes of cryptocurrency financing of terrorism and armed aggression and finding ways and means of solving problematic issues, because cryptocurrency financing of terrorism and armed aggression is an encroachment on national security. The methods of system analysis and technical- legal analysis, as well as the formal-logical method, were used in the research process. Thanks to this, approaches to understanding the way of committing crimes of the researched category have been determined. The shortcomings in the legal regulation of the circulation and use of cryptocurrency in Ukraine, as well as in the legal regulation of the investigation of crimes related to the illegal acquisition and use of cryptocurrency for criminal purposes, including for the financing of terrorism and armed aggression, are highlighted. Jurisdictional problems of criminal prosecution of persons who committed crimes of this category, their high latency due to the lack of proper legal procedures and methods of investigation, have been determined. The need to create specialized units in law enforcement agencies, whose competence will include the detection and investigation of the specified crimes, their active interaction with the Cyber Police, is substantiated. The attention and necessity of introducing a system of constant monitoring of social networks, the Internet, and media and conducting OSINT-intelligence from open sources with the aim of detecting and stopping such criminal activities, tracking and arresting and eventually seizing cryptocurrency, if such an opportunity is available, was emphasized. Practical recommendations for the investigation of crimes of cryptocurrency financing of terrorism and armed aggression have been formulated. The need for international legal cooperation in this area was emphasized; the need to involve specialists in the field of information technologies, programming, and blockchain engineering in the investigation process in general and in specific investigative actions. The requirements for the recording of evidence in the protocols of investigative (search) actions during the investigation of crimes of this category are formulated, in particular, the need for hashing of files is specified. The practical significance of the study is that the obtained results can be used during the investigation of crimes of the studied category