This article proposes a contemporary and innovative approach to portfolio efficiency, aiming to approximate a state of antifragility during periods of heightened geopolitical uncertainty and accelerated technological transformation. The multidisciplinary analysis draws on academic literature, European regulatory frameworks (such as MiCA), reports from international institutions including the World Economic Forum and the International Monetary Fund, as well as conceptual and technical documentation developed by leading platforms in the Web3 ecosystem. In preparing for the transition into a new technological era, the authors present a framework for real estate tokenization through converting property ownership into NFTs and using these tokens as collateral for lending in digital currencies. This approach addresses the problem of low real-estate liquidity and creates conditions for democratizing investment by enabling a low entry threshold and fractional ownership. The model’s antifragility is demonstrated through quantitative analysis, including an evaluation of portfolio volatility and efficiency based on Markowitz theory and the Sharpe ratio, with the results confirming the logic of Taleb’s barbell strategy. The study supports the potential for Bulgaria to position itself as an innovative regional hub for the development of Web3 and the tokenization of real-world assets.
A comparison of average Bitcoin prices in US dollars and average Wolf numbers for the solar cycle average for 2009–2025 allowed us to construct a model that explains 63.22% of the data variance. The author predicts a decline in the average annual Bitcoin price in 2026 and 2027.
Existing theories of decentralized systems—typified by blockchain consensusprotocols and distributed autonomous organizations—universally harbor a foundational presupposition: governance rules and protocol structures are fully specifiedprior to system operation, and evolution occurs only within the parameter spaceof those rules. This paper systematically demonstrates the theoretical limits ofthis “fixed protocol” preset, pointing out that when the rules themselves becomethe focal point of conflict, traditional analytical frameworks lack the conceptualresources to address the situation. By integrating the bounded rationality tradition from decision theory with the self-organization ideas from complexity science,this paper proposes “cognitive ecosystem” as an alternative theoretical framework,reconceptualizing participants in decentralized systems as autonomous agents holding evolvable cognitive architectures, and redescribing the system as a whole as afield of structural coupling among multiple cognitive architectures. Under thisframework, forks are not system failures but legitimate expansions of conceptualspace, and consensus is not unanimous agreement but functional differentiationacross cognitive niches. The paper demonstrates the explanatory power of thisframework through the cases of the Bitcoin block size war of 2015–2017 and the2016 The DAO incident, and discusses its further application prospects in the governance of digital infrastructure.
The article examines the problem of formalizing investment cash flow in a distributed ledger environment. Within the framework of the digital transformation of financial relations, the cash flow of an investment project can be represented as a digital twin, recorded in the distributed ledger infrastructure and implemented through smart contracts. The aim of the study is to develop a mathematical model of the digital twin of investment cash flow and an algorithm for its forecasting using neural networks. Theoretical approaches to the interpretation of digital twins are systematized, and the limitations of the classical discounted cash flow model in relation to the digital environment are analyzed. A formalized model of digital cash flow is proposed, taking into account transaction fees of the distributed ledger, algorithmically accrued income, and an extended discount rate structure including technological and regulatory risk premiums. An algorithm for neural network forecasting of the digital twin is developed based on a feature vector integrating financial and infrastructure parameters. A comparative analysis of the digital and classical models is performed, which allowed establishing the structural modification of the investment process in the digital environment. The obtained results can be used in the valuation of digital financial assets and the construction of adaptive systems for forecasting their cash flows.
In March 2026, researchers at Google Quantum AI published resource estimates showing that the elliptic-curve cryptography used by Bitcoin, Ethereum, and many other major blockchains could be broken with far fewer quantum-computing resources than previously believed. The authors validated their estimates through a zero-knowledge proof while withholding the underlying circuits. Within two months, an independent researcher reproduced the circuits and a public challenge improved on them. The quantum threat to digital assets has moved from a remote theoretical concern to a concrete migration problem. At the same time, U.S. policymakers are integrating quantum-vulnerable blockchain infrastructure into the financial system through federally regulated stablecoins, chartered crypto institutions, exchange-traded products, and tokenized securities. This Article examines the collision between those policy trajectories. It argues that financial stability should govern the response and that the federal objective should be containment of transmission from a failing legacy network into regulated finance. Congress should create a quantum-resilience perimeter under which covered intermediaries, stablecoin issuers, investment products, and market infrastructures may, after a defined transition, operate only through networks and digitalasset arrangements certified as quantum-resilient. Qualification should require protection of every material cryptographic function and a credible plan to prevent mass unauthorized monetization of assets controlled by deprecated credentials. Protocol communities would retain authority to choose the technical method, including migration, quarantine, recovery, rate limits, issuer-led reissuance, or permanent unspendability. Nonqualified networks could continue through self-custody and peer-to-peer use, but they would remain outside regulated custody, collateral, derivatives, tokenized markets, and U.S.-regulated dollar channels. The proposal thus protects financial stability without directing consensus rules or prohibiting private ownership.
Quantum computing is forcing law, technology, and public policy to confront a new category of dual-use knowledge: cryptanalytic research that may advance science while accelerating the capacity to compromise public cryptographic infrastructure. For decades, the risk that a sufficiently powerful quantum computer could break RSA and elliptic curve cryptography (ECC) remained a largely theoretical concern. That era of theoretical comfort is ending; quantum computing is moving from theoretical risk toward practical consequence. Specifically, recent work in quantum algorithms, resource estimation, quantum error correction (QEC), and architecture-specific implementation suggests that cryptographically relevant quantum computers may be closer, and may require fewer resources, than earlier assumptions suggested. In April 2026, Google Quantum AI and collaborators released a white paper estimating resources for quantum attacks on elliptic curve cryptography used, for example, in cryptocurrencies, including Bitcoin, while using a zero-knowledge-proof mechanism to support verification of the reported computation without disclosing attack-enabling implementation details. The Article proposes a hybrid governance model: preserve a strong presumption of publication; adopt voluntary quantum cryptanalysis disclosure norms; recognize zero-knowledge-proof-backed verifiable nondisclosure as a legitimate scholarly publication mechanism; establish an advisory Quantum Cryptanalysis Review Board (QCRB); clarify export-control treatment of quantum cryptanalysis; require quantum-risk impact statements for federally funded research; and tie disclosure norms to post-quantum cryptography (PQC) migration readiness. These proposals should not be understood as advocating broad, restrictive regulation of quantum-computing technologies, which would be premature and could harm innovation. The objective should not be secrecy for its own sake, nor government control of quantum research. Rather, law and policy should encourage voluntary action, scientific self-governance, and cooperation across the quantum-computing ecosystem while reducing unnecessary public alarm, avoiding premature weaponization, and accelerating migration to quantum-resistant solutions and systems.
This thesis examines the implications of market frictions in international finance and macroeconomics in three contexts. The first chapter documents the effect of trading relationships on client trading outcomes in the over-the-counter (OTC) foreign exchange (FX) derivatives market. The second chapter documents the effect of nominal wage setting frictions on employment. The third chapter examines the behavior of non-U.S. central banks when firms engage in currency mismatch, borrowing more in dollars than given by their dollar operating exposures, emphasizing how imperfect regulation may affect U.S. dollar interest rates. In the first chapter, joint with Gerardo Ferrara, I study whether clients that rely more heavily on a dealer in the OTC FX derivatives market have worse trading outcomes after the dealer is adversely shocked. Using granular transaction-level data, we document that trading relationships are persistent—in an active trading week, clients are more likely to trade with a dealer that they had a relationship with and relied on more heavily. Then, we exploit the March 2023 collapse of Credit Suisse as an exogenous shock to exposed clients’ set of trading alternatives when relationships are persistent. Using difference-in differences analyses, we find that, although Credit Suisse’s EURUSD notional traded and trade count declined, clients that relied less heavily on Credit Suisse did not differentially reduce their Credit Suisse-specific trading activity relative to more reliant clients. Instead, more reliant clients continued trading at the client level and increased activity with other existing dealer relationships without incurring additional costs, relative to less reliant clients. These findings suggest that search and bargaining frictions were not particularly costly for heavily reliant clients after the shock—relationship persistence did not differentially prevent them from reallocating activity to existing alternative dealers, or lead to relatively greater costs, when their relationship dealer came under stress. In the second chapter, joint with Gert Bijnens, Hugo Monnery, and Laura Nicolae, I empirically document the effect of wage changes, driven by wage indexation to inflation, on firm-level employment growth. In Belgium, nearly all employees’ wages are indexed to inflation and firms are grouped into labor agreements that determine the exact timing and frequency at which wages are indexed, e.g. every year or every month. Using firm-level administrative data, we estimate two-stage least squares regressions of firm-level employment growth on wage growth, instrumented by the wage growth implied by the firm’s indexation policy. We find that employment contracts by 0.4% over four quarters for each 1% increase in wages. This result is robust to including NACE sector-date fixed effects and to using only variation in firms’ indexation timing, controlling for their chosen indexation frequency. About one-third of the response comes via anticipation of future wage increases. The elasticity is more than twice as large in magnitude in the post-pandemic period than before it, suggesting strong nonlinearities. Overall, these results show that, by preventing inflation from reducing real wages, inflation indexation reduces employment. In the third chapter, joint with Mitali Das, Gita Gopinath, Taehoon Kim, and Jeremy Stein, I document an externality of central banks’ imperfect regulation of firms that engage in currency mismatch, which results from central banks’ dollar reserve accumulation decisions. We explore how foreign central banks behave when firms engage in currency mismatch. Using a panel of 56 countries, we document that central bank holdings of dollar reserves are correlated with the dollar-denominated bank borrowing of their non-financial corporate sectors. Then, we build a model in which the central bank can deal with private-sector mismatch, and the associated risk of a domestic financial crisis, by: (i) imposing ex ante financial regulations; or (ii) accumulating dollar reserves to serve as an ex post dollar lender of last resort. The model highlights a novel externality: individual central banks may over-accumulate dollar reserves, relative to what a global planner would choose. Under imperfect regulation of currency mismatch, individual central banks do not internalize that their hoarding of reserves exacerbates a global scarcity of dollar-denominated safe assets, which lowers dollar interest rates and encourages firms to further increase the currency mismatch of their liabilities. Relative to the decentralized outcome, a global planner may therefore prefer higher capital requirements and reduced holdings of dollar reserves.
The growth of the crypto markets has changed the investment environment in a profound manner by elevating cryptocurrencies from purely speculative assets to institutional-grade investments. The current paper evaluates the investment characteristics of Bitcoin and Ethereum, the most popular cryptocurrencies, based on the modern portfolio theory framework. According to the analysis carried out for 2020-2025, the Bitcoin asset demonstrates an impressive Sharpe ratio of 1.7, substantially exceeding that of the S&P 500 (0.54) and gold (0.48-0.54). In favorable market conditions, Ethereum outperforms Bitcoin in terms of risk-adjusted returns, exhibiting even better characteristics. The study highlights a change in the mechanism of price fluctuations in the market from the \\\"four-year cycle\\\" to the flow of institutional capital. At the same time, correlation analysis shows that despite the absence of high correlation of these assets with other asset classes over the long term, the correlation between the two increases under market pressure. As a result, 1-4% of portfolio weight can be safely allocated to each asset, depending on the investment strategy.
Historical Context and Problem Statement The digital revolution has created two parallel challenges that have resisted comprehensive solutions: Internet Data Transfer Limitations: Despite decades of progress, internet download speeds remain constrained by inefficient protocols that don't adapt to network topology dynamics. Traditional download managers like IDM operate with static segmentation strategies that ignore the quantum-inspired probabilistic nature of network paths. Web3 Liquidity Fragmentation: Decentralized finance (DeFi) suffers from fragmented liquidity across multiple venues, resulting in significant MEV exploitation. As documented by Qin et al. (2021), MEV extraction has cost users over $680 million in 2021 alone, with no comprehensive solution addressing the root cause. These seemingly disconnected problems share a common underlying structure: both involve the transfer of "value" (data or financial assets) across complex networks where efficiency is hampered by non-resonant transmission strategies.
Theoretical background: In general, authors claim that the business model for any human-beings organisation defines who and how creates values in a socio-economic context. Taking into account the organisational theories presented in literature, authors notice a variety of definitions and components of business models. In addition, values in the business models have different interpretations. By definition, decentralised autonomous organisation (DAO) is using the Blockchain 2.0 technology, which strongly supports its internal operational management, change of attitude towards organisation members’ identification, and controlling internal activities. Purpose of the article: Construction of the Decentralised Autonomous Organisation (DAO) business model for determining DAO strategic development is the main purpose of this study. The authors aim to provide their own proposal of business model, as well as the identification of DAO business model components. The authors expand the DAO business model canvas, and beyond variables included in Osterwalder’s model, and consider some other important DAO features by example of TalentDAO case study. Research methods: The authors have focused on surveys of the management science literature in some popular repositories. Beyond that, they have added a DAO case study. They have done descriptive analysis of publications on business models and DAO business models. The authors applied the case study approach, because they argue that each DAO is different and taking into account suggestions provided by practitioners, the exploratory case study method is the best method to reveal idiosyncrasy of business organisation as well as applicability of theoretical business models for practice of DAO management. Main findings: Through the literature surveys, authors concluded that selected theories in science of management are fundamental for DAO construction and applicable for development of business models. Although the reviewed models are various, they have many common features and allow constructing the authors’ model of DAO business, which is an extension of Osterwalder Business Model Canvas. The authors characterised DAO partners, customers, values, resources, and activities. The authors discussed constraints and risks of DAO activities as well as the applied methods of coordination and control. The authors claim that DAO supports decentralized decision-making and intra-organizational trust intensification. They argue that the case study on DAO business model is an exemplification, which can be useful for development of other similar DAOs.
Ejiro U, Osiobe, Waleed A., Hammood, Safia, Malallah, Nyore E., Osiobe · 6 authors
Quantum mechanics principles underpin quantum computing, signaling a major shift in how we process information. While it offers immense processing power and potential advantages, it also presents significant challenges for the cryptocurrency industry. This sector has grown rapidly, supporting decentralized finance and empowering users worldwide, but it also attracts malicious actors looking to exploit its vulnerabilities. Traditional cryptography remains strong, yet increasingly sophisticated computational attacks threaten security. As the cryptocurrency market expands, quantum computing offers both opportunities, such as improved transaction security, and risks, like easier decryption for hackers. Understanding quantum technology’s benefits and challenges is crucial as it develops. Currently, data is protected by traditional cryptography, but future, more powerful quantum computers could weaken this security. This article explores potential uses of quantum computing in daily life and business, explains its functions simply, and discusses societal impacts. Its goal is to help students and general readers understand how quantum technology might transform our world through clear language and real-life examples. Topics include the basics of quantum computing, its present and future applications across industries, and its societal effects. We provide a thorough analysis of how quantum computing could reshape society through mathematical insights, practical examples, and future perspectives.
Mazin Abed Mohammed, Mohd Khanapi Abd Ghani, Israa Badr Al-Mashhadani, Sajida Memon · 7 authors
The exponential growth of healthcare Internet of Things (IoT) data necessitates secure, low-latency analytics that extend beyond centralized architectures. This paper presents BDAFL DNN, a blockchain-integrated data analytics framework that combines Federated Learning (FL) and Deep Neural Networks (DNNs) for real-time, privacy-preserving healthcare analytics across edge and cloud resources. Local devices such as smartwatches and phones collect noninvasive time series sensor streams (heart rate, temperature, and abdomen sensors), perform on device DNN training, and send only model updates to healthcare edge nodes, where a blockchain ledger validates updates for integrity and traceability; validated updates are then aggregated in the cloud via FL to produce a global model without sharing raw data. In a simulation study against representative baselines, BDAFL DNN reduced execution time, energy use, and resource consumption, lowered the deadline miss ratio, and improved blockchain validation correctness. These results show that integrating blockchain with FL-driven edge and cloud DNN analytics can deliver scalable, secure, and timely insights for future healthcare IoT systems. Reason for Expression of Concern:The Editors wish to alert readers to potential concerns regarding the reliability of the findings reported in “Blockchain-Powered Dynamic Segmentation in Personal Health Record”. The journal has initiated an additional editorial assessment of the article’s methodology, data provenance, and reported outcomes to confirm their reliability and reproducibility. This notice is issued to ensure transparency while the review is ongoing. The Expression of Concern does not constitute a final determination regarding the validity of the work. The journal will update readers once the assessment is completed and will take any necessary editorial action in accordance with the journal’s policies and COPE guidance.See expression of concern available at:https://doi.org/10.58496/2026/017 https://mesopotamian.press/journals/index.php/CyberSecurity/article/view/1041
Krypto-Assets sind mit der zunehmenden Beliebtheit von Kryptowährungen ein verbreitetes Anlageprodukt geworden. Das Ziel der Arbeit besteht darin, das Konzept der Blockchain mit entsprechender technischer Umsetzung zu erläutern, die Investitionseigenschaften anhand einer Analyse aufzuzeigen und die Auseinandersetzung mit häufigen Kritikpunkten. Die empirisch‑quantitative gewonnenen Daten liefern im Betrachtungszeitraum von 01.02.2018 bis 31.01.2025 folgende Erkenntnisse: Kursentwicklung: Bitcoin (1010%) weist die höchste Performance auf und übertrifft damit Ethereum (211%) um das Fünffache, den S&P 500 (114%) um das Neunfache. Tether (2%) fokussiert keine Rendite, sondern Stabilität, dient daher nur als Referenz. Volatilität: Ethereum (1.9) hat den höchsten Spitzenwert für die rollierende Volatilität im 30-Tage-Fenster, gefolgt von Bitcoin (1.5). Einem vergleichbaren Bewegungsmuster folgen der S&P 500 (0.85) und Tether (0.15) und finden ihre Extremstelle ebenso im ersten Halbjahr 2020. Die deutlich geringere Schwankungsanfälligkeit des S&P 500s ist auf die höhere Diversifizierung durch die dahinterstehenden Wertpapiere zurückzuführen, bei Tether aufgrund der direkten Wertkoppelung an US-Dollar. Rendite-Risiko-Verhältnis: Bitcoin (35%) weist in der jährlichen Betrachtungsform die höchste annualisierte Rendite auf, gefolgt von Ethereum (15%), dem S&P 500 (10%) und Tether (0.003%). Die annualisierte Standardabweichung beschreibt das Risiko und wird von Ethereum (2.11) angeführt, darauffolgend Bitcoin (1.21), der S&P 500 (0.19) und Tether (0.008). Im sich daraus ergebenden Rendite-Risiko-Verhältnis führt der S&P 500 (0.39), danach folgen Bitcoin (0.26), Ethereum (0.04) und Tether (-3.21). Somit liefert der S&P 500 trotz geringerer Performance das beste Verhältnis aus Rendite und Risiko, was auf das deutlich geringere Risiko zurückzuführen ist. Korrelation: Bitcoin und Ethereum haben die höchste Korrelation (0.81), da beide als Kryptowährungen den gleichen Marktbedingungen ausgesetzt sind. Die Differenz zu 1 ist auf Einflüsse zurückzuführen, die das Asset selbst betreffen. Der S&P 500 korreliert leicht mit Ethereum (0.3) und Bitcoin (0.28). Die geringste Korrelation weist Tether auf, im Zusammenhang mit Bitcoin (0.01), dem S&P 500 (0.01) und Ethereum (0.02). Maximum Drawdown: Ethereum (90%) hat den höchsten Verlust im Vergleich zum Höchststand. Darauf, ebenso zu Jahresende 2019, folgt Bitcoin (70%), der S&P 500 (30%) zu Beginn des Jahres 2020 und Tether (5%) Ende 2019. Gesamtbewertung: Statistisch weist Bitcoin im Vergleich zu Ethereum höhere Renditen bei geringerem Risiko auf. Die geringere Korrelation von Bitcoin mit klassischen Anlageprodukten wie dem S&P 500 kann eine Diversifikationsfunktion begründen. Haftungsausschluss: Diese Thesis dient ausschließlich akademischen Zwecken. Trotz größter Sorgfalt bei der Erstellung kann keine Gewähr für die Richtigkeit und Vollständigkeit der enthaltenen Informationen übernommen werden. Der Autor übernimmt keine Haftung für Folgen, die sich aus der Verwendung dieser Arbeit ergeben. Disclaimer: This thesis is intended for academic purposes only. Although care has been taken to ensure the accuracy and completeness of the information, no guarantee is made that it is free of errors or omissions. The author assumes no responsibility for any consequences arising from its use.
Quantum computers pose a significant threat to blockchain technology's security, which heavily relies on public-key cryptography and hash functions. The cryptographic algorithms used in blockchains, based on large odd prime numbers and discrete logarithms, can be easily compromised by quantum computing algorithms like Shor's algorithm and its future qubit variations. This survey paper comprehensively examines the impact of quantum computers on blockchain security and explores potential mitigation strategies. We begin by surveying the existing literature on blockchains and quantum computing, providing insights into the current state of research. We then present an overview of blockchain, highlighting its key components and functionalities. We delve into the preliminaries and key definitions of quantum computing, establishing a foundation for understanding the implications on blockchain security. The application of blockchains in cybersecurity is explored, considering their strengths and vulnerabilities in light of evolving quantum computing capabilities. The survey focuses on the quantum security of blockchain's fundamental building blocks, including digital signatures, hash functions, consensus algorithms, and smart contracts. We analyze the vulnerabilities introduced by quantum computers and discuss potential countermeasures and enhancements to ensure the integrity and confidentiality of blockchain systems. Furthermore, we investigate the quantum attack surface of blockchains, identifying potential avenues for exploiting quantum computing to strengthen existing attacks. We emphasize the need for developing quantum-resistant defenses and explore solutions for mitigating the threat of quantum computers to blockchains, including the adoption of quantum and post-quantum blockchain architectures. By examining vulnerabilities and discussing mitigation strategies, we aim to guide researchers, practitioners, and policymakers in developing robust and secure blockchain systems capable of withstanding advancements in quantum computing technology.
Background: This paper analyses the influence of fluctuation in gold market on bitcoin prices. Based on previous studies, in present market conditions, volatility in gold prices have caused price changes in several other major assets in the market, such as crude oil. Gold fluctuations are likely to stimulate uncertainty in some other major assets. As bitcoin is becoming an alternative tool to hedge against inflation likewise to gold, the degree of uncertainty in bitcoin market is relatively high. Therefore, the study of causal relationship between gold and bitcoin markets has become appropriate since bitcoin has tremendous growth in its returns and shares many similarities with gold. Thereupon, this study reveals the evidence of Granger causality regression in different time spans to understand the relationship between gold and bitcoin. This relationship is beneficial to study since Granger causality hypothesis acknowledges whether gold’s historical prices are useful for forecasting the bitcoin market. Purpose: This study aims to analyze the relationship between gold and bitcoin market during an 8-year period from 2014 and 2022. Throughout this period, time spans which involves financial crises have been separated from the data set and tested separately to determine if there is a constant relationship between the variables. Through this, it has been intended to find the Granger causality link between gold and bitcoin market to see whether one is leading another one. Identifying the Granger causality correlation helps analyzing the patterns of correlation by using the empirical datasets, and to determine the strength of the Granger causal relationship’s nature between gold and bitcoin. Since the correlation itself does not explain why or how, but only if both markets move together, the Granger causality correlation between gold and bitcoin is the quantification of the impact that gold market performance has on bitcoin’s future price performance. Method: Since the collected data is time-series data, Augmented Dickey-Fuller tests have been conducted initially to the chosen tests. Following the results from ADF tests, Spearman’s Rho, iand Johansen’s Cointegration tests have been utilized to determine the long-term correlation between variables. Thereafter, Toda & Yamamoto and Dolado & Lütkepohl Granger Causality (TYDL-GC) method has been used to analyze the Granger causality link between the variables. Conclusion: The results of this study indicates that (i) no statistically significant correlation between gold and bitcoin market has been found according to the Spearman’s Rho test results, (ii) no long-term relationship has been found between gold and bitcoin according to cointegration test, (iii) gold does Granger Cause bitcoin prices. The evidence of causality link is unilateral from gold towards bitcoin market. Furthermore, it was observed that the Granger causality link weakens in short term and is not constant over time. The results fail to support the semi strong Efficient Market Hypothesis form. Thus, gold and bitcoin’s markets are efficient in the weak form but inefficient in the semi strong form. Since Granger causality has been found from gold towards bitcoin, one can construct a prediction model for bitcoin by using gold’s historical prices.
Альона Ільдусівна Гнатовська, А. І. Гнатовська, Алена Ильдусовна Гнатовская, Alona I. Hnatovska · 16 authors
The article deals with the problems of determining the place of the cryptocurrency in the system of financial instruments and the study of its legal status in Ukraine and in the world. The problems of influence of cryptocurrencies on the economy of Ukraine and other countries across the world, potential threats posed by the cryptocurrency system for users of such systems and ways of legal regulation of cryptocurrency transactions are considered. The terminology that is widely used in the cryptocurrency field is analyzed, the main types of cryptocurrencies and the technologies on which they function are considered. Their characteristic features, positive and innovative concepts, which were introduced with their appearance, are identified. The legal status of cryptocurrencies and their prevalence has been investigated. The modern concepts of regulation of the cryptocurrency market in Ukraine and in the world are characterized. In the course of researching the subject of the article, the authors conclude that it is necessary to establish state control over the regulation of the legal status of cryptocurrency and prevent its possible negative impact on the country's economy. It was also concluded that a draft law would be considered that would address the issue of regulation and control of cryptocurrency transactions.
Ayushi Sharma, Shashwat Tiwari, Nitin Arora, S. C. Sharma
Blockchain is an emerging technology that can radically improve transactions security at banking, supply chain, and other transaction networks. It's estimated that Blockchain will generate $3.1 trillion in new business value by 2030. Essentially, it provides the basis for a dynamic distributed ledger that can be applied to save time when recording transactions between parties, remove costs associated with intermediaries, and reduce risks of fraud and tampering. This book explores the fundamentals and applications of Blockchain technology. Readers will learn about the decentralized peer-to-peer network, distributed ledger, and the trust model that defines Blockchain technology. They will also be introduced to the basic components of Blockchain (transaction, block, block header, and the chain), its operations (hashing, verification, validation, and consensus model), underlying algorithms, and essentials of trust (hard fork and soft fork). Private and public Blockchain networks similar to Bitcoin and Ethereum will be introduced, as will concepts of Smart Contracts, Proof of Work and Proof of Stack, and cryptocurrency including Facebook's Libra will be elucidated. Also, the book will address the relationship between Blockchain technology, Internet of Things (IoT), Artificial Intelligence (AI), Cybersecurity, Digital Transformation and Quantum Computing. Readers will understand the inner workings and applications of this disruptive technology and its potential impact on all aspects of the business world and society. A look at the future trends of Blockchain Technology will be presented in the book.
Stephen Chan, Jeffrey Chu, Yuanyuan Zhang, Saralees Nadarajah
In financial trading, cryptocurrencies like bitcoin use decentralization, traceability, and anonymity features to perform transactional activities. These digital currencies, using the emerging blockchain technologies, are forming the basis of the largest unregulated markets in the world. This creates various regulatory challenges, including the illicit purchase of drugs and weapons, money laundering, and funding terrorist activities. This chapter analyzes various legal and ethical implications, their effects, and various solutions to overcome the inherent issues that are currently faced by the policymakers and regulators. The authors present the result of an analysis of 30 recently published peer-reviewed scientific publications and suggest various mechanisms that can help in the detection and prevention of illegal activities that currently account for a substantial proportion of cryptocurrency trading. They suggest methods and applications that can also be used to identify the dark marketplaces in the future.