Bitcoin transactions is gaining strength in the global economic landscape, including in Indonesia, as a consequence of the development of financial technology and the decentralization of the digital economy. Positive facts indicate that Bitcoin offers an alternative investment and transaction instrument with characteristics of transparency, speed, and minimal cross-border costs. However, negative facts that cannot be ignored are Bitcoin's value volatility , the potential for money laundering, and weak legal protection for users. In a social context, Bitcoin creates segregation between digitally savvy groups who benefit from it and conventional groups who are increasingly marginalized due to limited access and digital literacy . This study uses a normative-juridical method with a legislative and conceptual approach to analyze the legal implications of Bitcoin use in the Indonesian economy. The research gap lies in the lack of normative studies linking crypto asset regulation to the social impact of class segregation in the digital society. To date, regulations have emphasized legality and transaction oversight without considering the dimension of social justice. The research questions are formulated as follows: first, what are the legal implications of Bitcoin transactions in the Indonesian economic system? Second, how is social segregation formed through the practice of Bitcoin use in society? The novelty of this research is its interdisciplinary analysis linking the legal regulation of digital businesses with the social realities created by Bitcoin adoption . Preliminary results indicate that although Bitcoin is recognized as a legitimate crypto asset for trading, its lack of legal tender status creates legal dualism and reinforces socio-economic gaps in society.
The primary purpose is to trace the progression of scholarly research on cryptocurrency taxation, uncovering prevailing patterns, influential contributors, yearly scientific output and citations, most relevant sources, thematic analysis and cooccurrence networks from 2010 to 2025. Leveraging a systematic search on Scopus, our final dataset comprises 115 unique documents, with the majority of publications being highly recent (average age of 2.95 years) and exhibiting a robust annual growth rate of 18.65%. The analysis reveals that the field is highly collaborative (average of 2.7 co-authors per paper) and gaining significant scholarly attention, as evidenced by a promising average of 9.548 citations per document. The thematic structure of the literature, mapped through keyword co-occurrence and strategic diagrams, identifies "cryptocurrency," "blockchain," and "bitcoin" as the core, most central themes. The research is highly multidisciplinary, with a strong focus on regulatory, legal, and financial challenges surrounding taxation, anti-money laundering, and the classification of digital assets. While a dominant research source exists, the high dispersion of publications across 85 distinct sources suggests a fragmented but rapidly maturing field.
Este artigo analisa o custo‑benefício energético de três mecanismos de consenso centrais no ecossistema de criptoativos: Proof‑of‑Work (PoW), Proof‑of‑Stake (PoS) e Proof‑of‑History (PoH) combinado a PoS, examinando como diferenças de consumo de energia se relacionam a segurança, desempenho e sustentabilidade econômica. A partir de dados recentes sobre consumo energético de redes públicas como Bitcoin, Ethereum antes e depois da transição para PoS e Solana, discute‑se em que medida a evolução dos mecanismos de consenso permite reduzir ordens de grandeza de uso de eletricidade por transação, sem necessariamente comprometer a segurança e a descentralização. A metodologia baseia‑se em revisão bibliográfica de estudos acadêmicos e relatórios técnicos sobre consumo de energia em blockchains, análise de estimativas consolidadas de uso anual de eletricidade e de energia por transação e discussão conceitual de trade‑offs entre eficiência energética, robustez criptográfica, requisitos de hardware e impactos regulatórios. Evidências indicam que o Bitcoin, ancorado em PoW, mantém consumo anual estimado em torno de 120–130 TWh, enquanto o Ethereum, após migrar para PoS em 2022, reduziu seu consumo em mais de 99%, passando a operar com menos de 0,01 TWh por ano. Relatórios de eficiência energética mostram que redes que combinam PoH e PoS, como a Solana, apresentam consumo de energia por transação da ordem de centenas de joules, inferior tanto a redes PoW quanto a muitas redes PoS, embora existam ressalvas metodológicas e discussões sobre centralização de infraestrutura. Conclui‑se que PoS e esquemas híbridos com PoH oferecem vantagens substanciais em termos de eficiência energética, mas a avaliação de custo‑benefício precisa incorporar conjuntamente segurança econômica, distribuição de poder, maturidade de ecossistema e alinhamento com agendas de sustentabilidade e descarbonização que tendem a moldar a evolução da infraestrutura Web3.<br>
Abstract: This paper examines how national cryptocurrency regulations affect cross-country Bitcoin price segmentation, local prices, and traded volumes. Using daily data for 22 countries since 2013, we apply a dynamic fixed effects framework to deviations from the law of one price (LOP), controlling for country-specific barriers and global shocks. We distinguish between regulatory frameworks that enhance market functioning (e.g., securities laws, payment system integration, regulatory sandboxes), pro-innovation policies, restrictive measures (e.g., banking bans), and anti-money laundering/countering the financing of terrorism (AML/CFT) rules. Our results show that comprehensive and pro-innovation frameworks reduce price deviations from the USD benchmark, lower local prices, and increase traded volumes, while banking bans fragment markets, depress prices, and reduce volumes. AML/CFT laws exert a consistent downward effect on prices regardless of global conditions. Threshold Auto-Regressive (TAR) models further reveal that highly regulated countries—whether supportive or restrictive—are more sensitive to macro-financial factors such as capital account openness, inflation, relative traded volumes, and remittances, indicating tighter links to the broader financial system. These findings suggest that regulation not only shapes domestic market conditions but also alters the transmission of global and macro-financial shocks into cryptocurrency markets.
AIGP-Σ (AI Governance Protocol — Sigma) is a post-quantum cryptographic identity and authorization framework designed for autonomous AI agents operating in multi-agent and agentic payment environments. The protocol suite consists of five interconnected specifications: WP-01: Core Protocol — ML-DSA (CRYSTALS-Dilithium) based identity anchoring with STARK zero-knowledge proofs via RISC0, Bitcoin blockchain timestamping, and a cryptographic Kill Switch mechanism for emergency AI halt. WP-02: Kill Switch — Formal specification of the HALT proof system enabling verifiable, tamper-proof shutdown of AI agents without revealing operational state. WP-03: SSL for Agents — A mutual TLS-equivalent handshake protocol adapted for AI agent-to-agent communication, providing forward secrecy and post-quantum resistance. WP-04: Agentic Payments — Authorization layer for autonomous financial transactions executed by AI agents, with cryptographic scope limitation and audit trails. WP-05: Multi-Agent Orchestration — Trust propagation and delegation model for hierarchical multi-agent systems with verifiable credential chains.
ABSTRACT This article explores the application of demurrage money, a concept developed by Silvio Gesell, into Web3. Demurrage money, designed to discourage the hoarding of currency and prevent economic stagnation and concentrations in wealth, offers a potential remedy for the problems of traditional fiat and gold‐backed monetary systems. The article presents an overview of Web3, highlighting its core principles such as being decentralized, permissionless, community governed, and programmable. It critiques the limitations of current Web3 cryptocurrencies, particularly Bitcoin and other networks that have emerged since. By design these networks enable excessive asset storage and face sustainability challenges such as governance centralization and inadequate ecosystem funding. The article proposes that the implementation of a network coin tax, as a form of demurrage, would help to incentivize productive economic activity, decentralize coin ownership, provide reliable funding for node operators and ecosystem development and create opportunities for large‐scale public goods funding. Various monetary supply models are discussed, evaluating their compatibility with demurrage systems. The article concludes that demurrage based economic systems could lead to more resilient, equitable and sustainable Web3 ecosystems that have significant potential for making a global societal impact.
Daily probability changes in Kalshi macro prediction markets forecast cryptocurrency realized volatility through two distinct channels. The monetary policy channel, measured by Fed rate repricing on KXFED contracts, predicts Bitcoin volatility in sample with t = 3.63 and p < 0.001 but exhibits regime dependence tied to the 2024-2025 rate-cutting cycle. The recession risk signal from KXRECSSNBER proves more stable out of sample, delivering an MSFE ratio of 0.979 with Clark-West p = 0.020. The inflation channel, measured by CPI repricing on KXCPI contracts, predicts altcoin volatility for Ethereum, Solana, Cardano, and Chainlink with t-statistics ranging from -2.1 to -3.4 and out-of-sample gains for Ethereum at MSFE = 0.959 with p = 0.010 and Solana at p = 0.048. Both the Bitcoin--Fed-dovish and Chainlink--CPI specifications survive Benjamini-Hochberg correction at q = 0.05. Orthogonalization and baseline comparisons against Fed Funds futures, Treasury yields, and the Deribit implied volatility index confirm that these signals carry information not embedded in conventional financial instruments. The sample covers ten Kalshi event series and six cryptocurrency assets over January 2023 to March 2026.
Der Text analysiert den tiefgreifenden Wandel des Finanzsystems in Zeiten der Digitalisierung. Er zeigt, wie private Fintechs und Krypto-Emittenten das staatliche Monopol der Regulierung und der Geldbereitstellung infrage stellen. Marktmacht entsteht durch Regulierungsversagen.
Threshold transactions in Bitcoin is an effective solution for vulnerability of wallets to the loss or compromise of secret keys. It also enhances the applicability of Bitcoin to include use-cases that require partitioning the trust among a set of parties. Currently, the threshold transactions on Bitcoin expose the actual signers within the group of participants. This poses a threat of wallet hacks or theft targeting these signers. To address this issue of privacy, we propose a novel protocol to create threshold transaction using a combination of on-chain locking and off-chain proof of knowledge. As Bitcoin currently does not support verification of zero-knowledge schemes, the proposed protocol uses a Trusted Third Party ( TTP ) to verify the proofs off-chain. The trust on the third party is only limited to its service of signing on behalf of the users. The main contribution is the development and applicability of a m-out-of-N proof of partial knowledge that maintains the privacy of the signers both on-chain from the transaction verifiers and off-chain from the TTP and other signers as well. The protocol leverages Taproot’s spending path flexibility to incorporate dual spending capabilities and employs off-chain zero knowledge Σ-protocols to prove knowledge of private keys without disclosing their associated public keys. Experimental analysis demonstrates improved scalability and privacy than the mainstream threshold signature schemes for Bitcoin. A formal analysis demonstrates and establishes the security goals of the proposed mechanism.
This paper examines the market maturation hypothesis in cryptocurrency markets through a three-stage analysis of the evolution of tail risk in Bitcoin (BTC) and Ethereum (ETH). Using daily closing prices from January 2015 to February 2026 for BTC (n = 4058) and November 2017 to February 2026 for ETH (n = 3015), we employ 365-day rolling windows—reflecting the continuous 24/7 operation of cryptocurrency markets—to trace the temporal dynamics of Value-at-Risk (VaR), Conditional Value-at-Risk (CVaR), and Maximum Drawdown (MDD). The empirical strategy combines (i) Newey–West trend tests on rolling risk metrics, (ii) regime-conditional analysis across market states (Bull, Bear, or Neutral) and volatility regimes (high/low uncertainty), and (iii) exceedance correlation analysis to capture asymmetric BTC–ETH tail dependence. The results are consistent with the market maturation hypothesis: all ten trend coefficients across both assets are statistically significant (p < 0.001), with linear time trends explaining up to 46.8% (BTC VaR1%) and 67.5% (ETH VaR1%) of variation in rolling tail risk. Sub-period comparisons confirm economically meaningful declines—BTC VaR1% fell by 22.0% and ETH VaR1% by 26.6% between the early and late subsamples. However, maturation is markedly asymmetric across uncertainty regimes: tail-risk reductions concentrate in low-uncertainty periods, whereas BTC MDD in high-uncertainty regimes shows no significant improvement (+1.0%, p = 0.176). Excess correlation analysis reveals a persistent and widening downside asymmetry (ρ− = 0.847 vs. ρ+ = 0.246 at the 90th percentile), with late-period upper-tail correlation turning negative (ρ+ = −0.175 at the 95th percentile), implying that portfolio diversification within the cryptocurrency asset class remains illusory during market stress. These findings carry direct implications for institutional risk management, stress-testing frameworks, and prudential regulation of digital assets.
Dr.B.Swathi Dr.B.Swathi, SAANIYA ARSHI, ARABOTHU ANVESH, MOHAMMED AYAAN AHMED · 5 authors
The quick adoption of blockchain technology and generative AI is a major factor in the world's electricity use, which raises concerns about their long-term environmental impact. To save energy, the first thing you need to do is figure out how much energy you are already using. But because blockchain and generative AI are both cloud-based services, it's not easy to understand how much energy they use when they're not at your site. This makes it harder for companies and organisations that want to improve the accuracy of calculating Scope 3 emissions. This study determines the energy consumption of these technologies at both the system level and per-use basis, comparing them to traditional services such as payment networks and web search engines. For instance, Bitcoin, which uses a Proof of Work (PoW) blockchain, uses about 121 TWh, or 0.43% of all the electricity used in the world. It also uses 720,000 times more energy per transaction than the Visa payment system. When Ethereum switched to Proof of Stake (PoS) in 2022, it used 99.988% less energy, showing how much more efficient things can be.Generative AI models also use a lot of energy, especially when they are being trained and used to make predictions. For instance, it took about 9,450 MWh of energy to train GPT-4, and it took more than 500 MWh of energy to do inference work every day. Inference, which is always powered by user activity, is often more resource-intensive than the training process. The authors say that we need to learn more about and lessen the environmental effects of these technologies right away. Possible solutions include energy-efficient consensus mechanisms or giving AIs the ability to better optimise their own lifecycle. The report is meant to help businesses think about how to use technology in a way that is good for the environment as part of a better or more complete Scope 3 emissions strategy.
ONU 2.0 is a next-generation global governance platform designed to coordinate publicpolicy, development projects, and multilateral philanthropy across BRICS+ member statesand international observer partners. Built on a hybrid architecture that combines traditionale-government systems with Web3 infrastructure and distributed artificial intelligence, itimplements a complete workflow of submission → GPS jurisdictional validation → multi-levelapproval pipeline → audited execution → on-chain anchoring.At the technical level, the platform is structured around seven architectural layers: GPSjurisdictional control, multi-level approval state machines, asynchronous message routing (AOprotocol), cryptographically chained audit ledgers, BRICS+ policy exchange, BitcoinOP_RETURN anchoring via Arkhe-Chain (Chain ID 2140), and Kuramoto oscillator-basednetwork coherence consensus. The AI module is implemented as a Bittensor fork — the ONU2.0 Subnet — with six specialized sub-networks for data validation, policy enforcement, auditsurveillance, subnet mining, sovereign identity, and ethical oversight.Philosophically, ONU 2.0 is grounded in the C/Z duality of the Arkhe(n) framework:governance as the projection of the field of possibility (C-domain: policy intent, legal norms,stakeholder consensus) into the field of actuality (Z-domain: executed transactions,immutable audit records, on-chain commitments). The Kuramoto coherence layeroperationalizes this philosophical premise — network governance achieves legitimacy whenthe synchronization of operator nodes crosses the critical threshold phi_c = 0.618.
Adegboyega Afolabi, Modupe M. Adesemowo, Olayemi O. Amosun, M. Olamide Otuyelu · 6 authors
As digital intermediation accelerates, Nigerian deposit money banks (DMBs) confront rising cyber-enabled fraud since the launch of Bitcoin in 2009, despite ongoing reforms. Most blockchain research still centres on cryptocurrencies, with relatively few studies examining their applications in other industries. This study investigates whether blockchain technology (smart contracts, permissioned distributed ledgers, and secure digital wallets) is associated with lower fraud in Nigerian DMBs.Using survey data from 120 bankers across five institutions spanning international, national, and regional licenses, we estimate Ordinary Least Squares (OLS) models relating each BCT dimension, and a composite index, to two outcomes: spread of fraud (SOF) and internet fraud activities (IFA). Reliability analysis shows strong internal consistency (α = 0.75–0.91). Models include robustness checks for multicollinearity and specification. Results indicate that higher perceived deployment of smart contracts, distributed ledger, and digital wallet capabilities is negatively and significantly associated with SOF and IFA; a composite BCT index positively predicts overall fraud-reduction assessments. These findings align with recent sectoral evidence that blockchain adoption lowers fraud-related costs and enhances transaction integrity in banking. Given Nigeria’s elevated incidence of electronic fraud in retail payments, the practical implication is that embedding programmable controls, tamper-evident shared records, and cryptographic authentication can harden high-risk processes. We recommend that regulators and DMBs advance permissioned BCT pilots integrated with Anti-Money Laundering (AML) and Know Your Customer (KYC) workflows, strengthen reporting standards, and build human-capital readiness. Beyond cryptocurrency, enterprise-grade BCT offers credible pathways to reduce fraud externalities and improve operational resilience in Nigeria’s banking sector. Keywords: Blockchain; Smart contracts; Distributed ledger; Digital wallet; Bank fraud; Nigeria.
This analysis examines the role of crypto-assets, particularly Bitcoin, in an investment portfolio. The crypto-asset market, with its rather rapid growth, has begun to attract the interest of a broad range of investors, and despite the uncertainties still existing in the legal framework regulating the sector, international experience shows that the involvement of institutional structures is also growing. The study investigates the impact of including Bitcoin – the largest crypto-asset – within a portfolio of traditional investment assets, focusing on the dynamics of portfolio risk-return indicators to reveal the investment potential of cryptocurrencies. Correlations with other assets were considered, and the possibility of constructing a Markovitz portfolio by including cryptocurrency in a traditional portfolio was considered. Within the framework of portfolio analysis, three scenarios were discussed to see the impact of cryptocurrency inclusion on the portfolio's risk-return indicators, Sharpe ratio. The results of the study generally confirm the hypothesis that cryptocurrencies can serve as a tool to enhance portfolio performance when included in a limited proportion.
Bitcoin and major precious metals are frequently discussed as hedges against equity drawdowns, inflation surprises, and policy uncertainty, which implicitly assumes a degree of functional equivalence in their risk behavior. Existing work remains limited in assessing high-dimensional dependence structures in the Bitcoin and precious metals system, without relying on bivariate conditional risk measures or restrictive copula frameworks. This study therefore aims to quantify bilateral and multivariate tail dependence and systemic spillovers between Bitcoin and selected precious metals and to identify the best-performing multivariate tail-risk specification, with model comparison conducted using AIC and BIC. The analysis uses 3,665 daily observations of adjusted closing prices spanning January 2013 to September 2024, sourced from Yahoo Finance. Marginal returns are fitted with an ARFIMA–FIGARCH skewed-t model, while cross-asset tail dependence is estimated via vine-copula quantile regression (C- and D-vines) using a 252-day rolling window (one-day step) with 10,000 copula simulations. Results indicate that Bitcoin exhibits substantially larger downside systemic contributions than precious metals, whereas gold displays the smallest systemic risk profile. Across information criteria, the D-vine–based SCoVaR specification provides the best overall fit, indicating that vine-based multivariate tail-risk measures better characterize systemic spillovers between the cryptocurrency and traditionally defensive assets under extreme market conditions. These results motivate future research on broader cryptocommodity networks and macro-financial conditioning, while practitioners and regulators can use the D-vine SCoVaR to monitor and mitigate downside spillovers in mixed-asset portfolios.
Cryptocurrency prices often move with narratives and investor sentiment. This paper builds a multilingual crypto sentiment index, ML-CryptoSI, using daily news text in six languages and Binance market data for BTC and ETH. We first aggregate language-level daily sentiment and then use PCA to extract the common component across languages. Next, we test whether ML-CryptoSI predicts next-day returns and volatility proxies after controlling for lagged market conditions, liquidity, and day-of-week fixed effects. The results show that ML-CryptoSI has incremental information for returns, especially for ETH, and the effect is stronger on high news-intensity days. In contrast, the evidence for volatility prediction is weak in this short sample. Overall, the findings suggest that the common factor in multilingual news sentiment matters for short-run crypto pricing and is state dependent.
The environmental externalities of crypto-assets―particularly the substantial electricity demand inherent in the energy-inefficient consensus protocol known as Proof of Work（PoW）―have attracted increasing attention in sustainable finance. However, despite the growing interest in the environmental impact of crypto-assets, a comprehensive integration of technical energy analyses with environmental, social, and governance（ESG） investment, financial regulation, and corporate disclosure remains limited. This study addresses this gap by analysing how the environmental impact of crypto-assets can be incorporated into emerging sustainability frameworks, drawing on empirically verifiable sources such as the Cambridge Bitcoin Electricity Consumption Index, the Corporate Sustainability Reporting Directive of the European Union（EU）, the standards of the International Sustainability Standards Board, and disclosure information by major mining companies. The analysis is conducted along three dimensions:（1） market reactions and the evolution of ESG evaluation;（2） trends in disclosure regulation; and（3） case studies of corporate disclosure practices. Moreover, the transition to more energy-efficient alternative consensus protocols—as exemplified by Ethereum’s adoption of Proof of Stake—is examined as empirical evidence of technological innovation aimed at mitigating environmental externalities. By integrating market, institutional, and technological perspectives, the study elucidates persistent challenges concerning the reliability, comparability, and completeness of sustainability-related disclosures, as well as regulatory consistency across jurisdictions. It thereby contributes to the literature from both theoretical and practical perspectives.
Under the influence of Industry 4.0, numerous scientific breakthroughs have emerged, including "cryptocurrencies and virtual currencies." Globally, various types of crypto-assets such as Ethereum, Litecoin, Bitcoin, Swisscoin, and Zcash have gained prominence, with regulatory approaches ranging from outright bans to formal authorization. This article examines the legal framework governing virtual currencies in Canada—a pioneer in establishing such regulations—to derive critical lessons for Vietnam in refining its legal framework for assets currently being drafted in the Law on Digital Technology Industry
Oliver Aleksander Larsen, Rasmus Stenbak Larsen, Mahyar Tourchi Moghaddam
Today's internet concentrates identity, payments, communication, and content hosting under a small number of corporate intermediaries, creating single points of failure, enabling censorship, and extracting economic rent from participants. We present BitSov, an architectural framework for sovereign internet infrastructure that composes existing decentralized technologies (Bitcoin, Lightning Network, decentralized storage, federated messaging, and mesh connectivity) into a unified, eight-layer protocol stack anchored to Bitcoin's base layer. The framework introduces three architectural patterns: (1) payment-gated messaging, where every transmitted message requires cryptographic proof of a Bitcoin payment, deterring spam through economic incentives rather than moderation; (2) timechain-locked contracts, which anchor subscriptions and licenses to Bitcoin block height (the timechain) rather than calendar dates; and (3) a self-sustaining economic flywheel that converts service revenue into infrastructure growth. A dual settlement model supports both on-chain transactions for permanence and auditability and Lightning micropayments for high-frequency messaging. As a position paper, we analyze the quality attributes, discuss open challenges, and propose a research agenda for empirical validation.
Abstract: This study investigates the dynamic relationships between Bitcoin, oil prices, and the US dollar (USD) using a Vector Autoregressive (VAR) model. Utilizing daily data from 2018 to 2023, the analysis reveals that both Bitcoin and oil prices exert significant short-term impacts on the USD, though these effects diminish over the long term. Bitcoin, characterized by its high volatility and safe-haven attributes, serves as an alternative asset during periods of economic uncertainty, while oil prices influence the dollar through trade flows and inflationary pressures. The findings highlight the transient nature of these interactions, with Bitcoin and oil acting as short-term pressure factors on the USD. These insights are crucial for investors and policymakers in managing risks and optimizing strategies in a volatile financial environment. This study contributes to the literature by providing empirical insights into the interconnectedness of cryptocurrencies, commodities, and currencies, offering valuable implications for financial decision-making. Keywords: Bitcoin, Oil Prices, US Dollar (USD), Vector Autoregressive (VAR) Model, Cryptocurrencies, Exchange Rates, Safe-Haven Assets JEL Classification Number: C32, E44, G15, Q43
Bitcoin has two cryptographic layers. SHA-256 secures mining and the hash chain — it has no periodicity, no rhythm, nothing for the quantum Fourier transform to detect. ECDSA secures signatures — it has rhythm, and Shor's algorithm breaks it. The foundation is quantum resistant. The signatures are not — but signatures are a software upgrade. The hash rate is not. Bitcoin is a shadow-mirror coupling: single hash (shadow, local, independent) coupled to blockchain (mirror, global, irreducible) through proof of work, with a self-regulating coupling constant κ ≈ 128,748 measured across 2,906 days and 12 orders of magnitude. Extended construction from Shadow & Mirror: Complementarity of Computation and Consciousness (Ross, 2026).
Money laundering in cryptocurrency networks poses persistent challenges for financial intelligence units due to the pseudo-anonymous architecture of blockchain systems and the limited effectiveness of conventional rule-based detection methods. This study introduces chaos theory and recurrence quantification analysis (RQA) as a novel framework for characterizing temporal behavioral dynamics in Bitcoin money laundering transactions. Analyzing 46,564 labeled transactions from the Elliptic Bitcoin Dataset spanning 2009-2018, we construct aggregate time series for illicit and licit transaction volumes across 49 discrete temporal steps, corresponding to the dataset’s inherent graph-based snapshot structure, and apply phase space reconstruction techniques to compute three RQA metrics: determinism (DET), laminarity (LAM), and entropy (ENTR). Results reveal paradoxically higher determinism in illicit transactions (38.24% vs. 16.67% for licit), substantially elevated laminarity (35.80% vs. 0.00%), and greater entropy (0.45 vs. 0.00%), indicating that sophisticated obfuscation strategies inadvertently introduce detectable deterministic signatures. Augmenting conventional graph-based features with RQA metrics significantly enhances Random Forest classification performance, reaching near-optimal levels (F1 = 1.000, AUC = 1.000) within the evaluated dataset environment, with entropy emerging as the single most discriminative predictor. While these exceptional results reflect the high fidelity of chaos-based features in capturing structured laundering patterns from this period, they serve as a benchmark for the theoretical potential of nonlinear analysis in blockchain forensics. These findings demonstrate that temporal complexity features offer a powerful diagnostic tool for real-time monitoring and detection of systemic financial crime in evolving cryptocurrency ecosystems.
BITCOIN AS A COMPONENT OF THE MONETARY SYSTEM: SOCIAL INTEGRATION, TECHNOLOGICAL DIFFUSION AND SOCIO-POLITICAL TRANSFORMATIONSThe aim of this article is a multifaceted analysis of Bitcoin as a component of the contemporary monetary system, identifying the processes of its socialization, technological diffusion, and the consequences of changes in the socio-political space. The author successively presents indicators of Bitcoin’s social and economic integration and the development of blockchain as a tool transforming trust, legitimization, and the structure of value circulation. Particular emphasis is placed on analyzing the process of blockchain technology diffusion and the social mechanisms of legitimizing new forms of value. The article concludes with the thesis that Bitcoin, transcending its financial function, has become a component of a broader civilizational shift – a harbinger of the transformation of the model of money, ownership, and sovereignty in the era of Web 3.0.