We study permissionless spot--perpetual basis trading in decentralized finance as a collateral control problem. The strategy holds spot inventory, hedges directional exposure with a short perpetual, and allocates capital between spot inventory and derivative margin under on-chain liquidity and execution frictions. The paper delivers three results. First, it solves a static control problem for the collateral share and shows that the risk-constrained formulation provides a more robust operating benchmark relative to the economic optimum. In comparative calibration, the required collateral rises monotonically under volatility stress. The collateral is the lowest for BTC and increases significantly for long tail assets such as LINK and DOGE. Second, the paper derives an asymmetric dynamic extension in which the lower boundary of intervention is solvency driven, and the upper boundary is determined by a trade-off between carry-loss and the cost of rebalancing. Monte Carlo simulation shows that the lower boundary remains structurally relevant, whereas meaningful interior upper triggers survive mainly in the regimes with high carry and low costs. Third, the paper validates an execution-aware implementation with live routed execution and historical backtests. The execution layer shows that the realized wedges are significant, but become worse in the case of selling the basis. This justifies a minimum effective rebalancing size and a positive execution buffer. The historical validation shows that in the case of a fixed control rule the realized performance is predominantly explained by the funding environment.
The article presents a comparative analysis of the stages of development of postgraduate teacher training (PTT) in Ukraine and four countries of the European Union (EU) (Poland, Finland, Germany, and France) for 1991–2024. The relevance of the study is determined by the need to modernize the national system of advanced training in the context of European integration, digitalization and reform of general secondary education. The research employed the following methods: content analysis of legislative acts, a chronological reconstruction of educational reforms, a comparison of postgraduate education models, a SWOT analysis of the Ukrainian system, as well as an analysis of financial costs (2020–2024). It is established that Ukraine implements a hybrid model with decentralization of financing and a 150-hour standard, while other countries apply decentralized (Poland, Germany) or centralized (France, partly Finland) approaches with an orientation towards digitalization, inclusiveness, and research methods. In 2024, the highest amount of spending on teachers’ professional development (advanced training) was found in Germany (€3,830 million), the lowest in Ukraine (€92.5 million). The scientific novelty of the study lies in the integrated comparison of financial, regulatory, and institutional aspects of postgraduate teacher training across Ukraine and four EU countries. The results can be used to form an adaptive model of teachers’ professional development in Ukraine. Received: 22 November 2025 / Accepted: 05 April 2026 / Published: May 2026
Abstract We introduce Koan, a system for compiling natural language DeFi requests into executable safety-validated directed acyclic graphs (DAGs). Assembling correct multi-step DeFi workflows requires sequencing irrevocable on-chain transactions across heterogeneous protocols, demanding flexible intent understanding and strict execution discipline simultaneously - a combination no existing tool provides. Koan addresses this in two phases. Phase 1 translates user intent into a typed graph via an LLM with deterministic fallback heuristics. Phase 2 validates that graph, injects missing safety nodes, and executes with dependency-aware scheduling. We evaluated on 1,000 prompts across 9 DeFi categories. Intent-to-workflow correctness reached 82.4%; DAG validity 93.6%. The Safety Injector raised price-impact check coverage from 41.2% to 98.4%, and 7.3% of all workflows were aborted by injected checks identifying excessive risk. Workflow authoring averaged 2.4 min versus 46.8 min for manual scripting (a 20x speedup), and compiled flows achieved 97% execution success with 18% gas savings on matched DEX routes under testnet conditions. Keywords Blockchain systems, decentralized finance, intent compilation, large language models, workflow orchestration.
This study aims to analyze and compare education financing systems in Finland, Japan, the United States, and Indonesia, with a focus on identifying key characteristics, philosophical differences, and policy implications of each model. The research employs a systematic literature review combined with comparative analysis, using management-oriented indicators including equity, efficiency, governance, and sustainability. Findings indicate that Finland implements a full public funding model emphasizing equity, Japan operates a hybrid model with high transparency, the United States exhibits significant disparities due to property-tax-based decentralization, and Indonesia remains in a transitional phase with challenges in fiscal capacity and governance accountability. The study highlights that successful education financing depends on consistent policy implementation, clear funding distribution formulas, and integrity in governance systems. The results provide actionable policy implications for improving national education financing, including the adoption of needs-based funding formulas, digitalized accountability systems, and diversified funding sources through public–private partnerships. By integrating management and governance dimensions, this study contributes to a better understanding of effective and equitable educational funding practices across diverse contexts.
As the Agentic Economy expands, autonomous AI agents—ranging from algorithmic trading bots on decentralized finance (DeFi) platforms to decentralized physical infrastructure (DePIN) orchestrators—operate with increasing autonomy. However, the absence of a standardized, cross-protocol identity and behavioral reputation layer exposes the ecosystem to coordinated agentic attacks. This paper presents Sigui, alongside the proposed Ethereum standard ERC-8259, which introduces a composable framework for Decentralized Identifiers (DIDs), dynamic reputation scoring, and trustless threat intelligence sharing specifically designed for AI agents operating on EVM-compatible networks. By decoupling identity verification, reputation mutation, and threat pattern hashing, Sigui enables smart contracts to perform zero-latency, on-chain risk assessments of agent transactions. We detail the architecture of the IAgentIdentity, IAgentReputation, and IThreatRegistry interfaces, propose a deterministic cryptographic hashing standard for multi-layered threat patterns, and discuss the economic security and sybil resistance of the protocol. The reference implementation, deployed on the Ethereum Sepolia testnet, demonstrates the feasibility of real-time A2A (Agent-to-Agent) security protocols.
Alexandre Pires Barbosa, Douglas Wegner, Rodrigo Pereira dos Santos
Research Context: Decentralized Autonomous Organizations (DAO) emerge as innovative structures operating on blockchain infrastructures, providing transparency, decentralization, and autonomy in digital governance and coordination processes. Scientific and/or Practical Problem: Despite their transformative potential, DAO face significant obstacles, such as scalability limitations, risks of power concentration, legal ambiguities, and complex incentive models. Proposed Solution and/or Analysis: This study investigates recent scientific literature on DAO, seeking to understand their current state, focusing on how they have been conceptualized, characterized, evaluated, and applied. Related IS Theory: The research draws on the wisdom of crowd theory, which explains how collective decision-making can overcome individual choices, and sociotechnical theory, which emphasizes the interaction between technological infrastructures and social structures. Together, these perspectives frame DAO as hybrid systems that integrate algorithmic processes with collective human governance. Research Method: A systematic mapping study was conducted, encompassing the collection, selection, and coding of 47 primary studies published in relevant scientific sources. Summary of Results: The results highlight the conceptual consensus on the decentralized and smart contract-based nature of DAO, propose categories of structural challenges, and map recurring application domains, such as decentralized finance (DeFi), open science, energy, and digital art. Furthermore, the results demonstrate the transition of DAO from algorithmic entities to sociotechnical hybrids, connected to emerging trends such as the metaverse, NFTs, and decentralized artificial intelligence. Contributions and Impact to IS area: This study provides an updated theoretical foundation for the IS area, mapping the state of the art of DAO, identifying structural challenges, and emphasizing their evolution toward hybrid models. Most importantly, it reveals the complexity and originality of uniting the three main pillars of information systems (code, governance, and automated processes), thus contributing to the design of more resilient, inclusive, and sustainable digital governance systems in emerging decentralized ecosystems.
The development of financial technology has led to the emergence of cryptocurrency as a decentralized digital instrument that enables fast and cross-border financial transactions. While this technology offers efficiency and flexibility in digital financial activities, it also creates opportunities for misuse in various forms of crime, including terrorist financing. This study aims to analyze the use of cryptocurrency as a means of financing terrorist activities in Indonesia, examine the existing legal framework governing terrorist financing, and identify the challenges faced in law enforcement. This research employs a normative legal method using statutory, conceptual, and case study approaches. The findings indicate that the use of cryptocurrency as a medium for terrorist financing still fulfills the elements of a criminal offense as regulated under Law Number 9 of 2013 concerning the Prevention and Eradication of Terrorism Financing. However, the characteristics of cryptocurrency, such as anonymity, decentralization, and cross-border transactions, create significant challenges in the processes of evidence gathering, transaction tracing, and identification of perpetrators. In addition, there is a regulatory gap between the recognition of crypto assets as economic commodities and the supervision of their potential misuse for terrorist financing. Therefore, stronger regulations are needed to explicitly integrate crypto assets into the terrorist financing prevention regime, along with improving the capacity of law enforcement agencies in blockchain transaction analysis and strengthening international cooperation to enhance the effectiveness of law enforcement in the digital economy era.
Smart contract vulnerabilities in Decentralized Finance caused over billions of dollars losses every year, yet the security community faces a critical bottleneck: identifying a vulnerability is not the same as proving it is exploitable. Manual PoC construction is prohibitively labor-intensive, leaving most disclosed vulnerabilities unverified and protocols exposed long before mitigation is applied. In this paper, we propose \sys, a knowledge-driven agentic system for end-to-end contract vulnerability detection and exploit synthesis. Our core insight is that exploit synthesis is not a code generation task but a \emph{structured reasoning problem} that requires grounded knowledge of protocol semantics, failure root cause, and exploit primitives. \sys organizes this knowledge into a \emph{Hierarchical Knowledge Graph} (HKG) that serves as structured memory for LLM-guided multi-hop reasoning. To validate exploit feasibility beyond code synthesis, \sys employs a two-stage validation framework that checks exploit-path reachability via SMT solving and profit realizability via asset-level state simulation, ensuring generated PoCs satisfy both logical and economic viability constraints. Evaluated on 88 real-world DeFi attacks and 72 audited projects (2,573 contracts), \sys achieves 98\% recall and 0.9 F1-score in detection, and a 96.6\% exploit success rate (ESR), reproducing 85 historical exploits and recovering over \$116.2M revenue. \sys outperforms SOTA fuzzers (\textsc{Verite}, \textsc{ItyFuzz}) by up to $5\times$ in ESR and $300\times$ in recoverable value, and the LLM-based exploit generator \textsc{A1} by $2\times$ and $8.5\times$ respectively. In bug bounty evaluation, \sys identified 16 confirmed 0-day vulnerabilities, helping secure over \$70.6M and earning \$2,900 in bounties.
India maintains its position as the central hub which has driven cryptocurrency from its initial experimental phase into a global financial revolution. India leads the world in blockchain adoption because it has 119 million crypto users, which makes it the top country for blockchain adoption. The nation enforces a 30 percent flat tax on Virtual Digital Asset earnings. This does not allow taxpayers to reduce their tax burden through loss deductions while it also requires a 1 percent Tax Deducted at Source. The paper analyzes how India has developed its regulatory framework and studies the Finance Act 2022 tax system impacts, and Digital Rupee expansion, and Web3 startup network, and decentralized finance potential for financial inclusion in India. The study shows that India allows about 60 percent of cryptocurrency transactions to occur outside its borders because of its current regulatory system, which is based on information from RBI publications and government policy documents, and Supreme Court rulings, and IMF and FATF reports, and Chainalysis and CoinSwitch industry data, and financial journalism until early 2026. The paper demonstrates that India requires a single regulatory framework, which provides fairness and clarity, and future-oriented guidance to achieve its digital asset economy potential.
This paper presents Polyquity, a Web2.5 platform enabling decentralized Initial Public Offering (IPO) fundraising through a hybrid data architecture. The platform leverages the Avalanche C-Chain for high-speed settlement, while utilizing a custom WebSocket indexer and PostgreSQL database to bridge the gap between blockchain security and institutional-grade user interfaces. By implementing a strict Role-Based Access Control (RBAC) model alongside modular architecture for auction mechanisms, fund escrow, and secondary market functions, Polyquity demonstrates how decentralized capital formation can achieve web2-equivalent performance while preserving core web3 security. The system utilizes the blockchain as the ultimate source of truth for state and funds, while the relational database serves as the source of speed for client-side rendering. Polyquity achieves sub-2-second transaction finality with 50% lower costs than Ethereum, supporting 10,000+ concurrent participants. This work establishes practical mechanisms for bridging traditional finance and decentralized ecosystems through a highly scalable, hybrid full-stack design.
Blockchain-based financial systems process billions in transactions but remain vulnerable to sophisticated fraud schemes. Current detection approaches analyze completed transactions, preventing neither fund loss nor protocol exploitation. We address this through an oracle-mediated prevention system integrating machine learning inference with smart contract execution. Training ensemble models on 12,847 Ethereum transactions with engineered features capturing gas anomalies and temporal patterns, we achieve 94.2\% fraud classification accuracy. Testnet deployment demonstrates 1.09-second response latency with 6.8\% computational overhead, contrasting favorably against prior on-chain implementations requiring 34\% overhead. Our working prototype validates practical viability for production environments where security requirements justify marginal transaction costs.
Renewable energy in Africa has gained increasing attention as a strategic pathway to achieving sustainable development, energy security, and economic transformation. A structured search of peer-reviewed studies was conducted using Web of Science, Scopus, and ProQuest. Fifteen empirical studies met the strict PRISMA inclusion criteria for detailed systematic synthesis, while additional high-quality review articles, book chapters, and policy reports were incorporated to strengthen contextual interpretation of renewable energy deployment trends across Africa. This systematic review synthesizes empirical evidence on renewable energy deployment across the continent, focusing on trends, challenges, and opportunities. Africa is endowed with abundant solar, wind, hydropower, geothermal, and biomass resources, yet actual utilization remains uneven and limited, with solar and wind experiencing the most rapid growth in recent years. Hydropower continues to dominate installed capacity, while geothermal and emerging technologies remain largely underdeveloped. Persistent barriers to deployment include inadequate grid infrastructure, limited access to finance, policy and regulatory inconsistencies, institutional capacity constraints, and political instability, particularly in rural and decentralized systems. Despite these challenges, opportunities exist in the form of declining technology costs, growing private and international investment, expansion of decentralized energy systems, and regional cooperation initiatives. Strengthening policy implementation, improving governance coordination, investing in infrastructure and human capital, and promoting innovative financing mechanisms are critical to accelerating Africa’s renewable energy transition.
This white paper introduces the Coherence Ledger, a decentralized and time-weighted integrity scoring system designed to evaluate individuals and organizations based on long-term behavioral patterns rather than short-term claims.It critiques existing trust systems—including online reviews, credit scoring, and professional directories—as structurally vulnerable to manipulation, opacity, retaliation, and extraction incentives.The framework proposes a transparent scoring protocol combining behavioral events, exponential time decay, decentralized identity verification, and peer-based trust propagation to create measurable coherence scores.It integrates technologies such as decentralized identifiers (DIDs), Soulbound Tokens, and web-of-trust mechanisms to reduce gaming, increase accountability, and preserve auditability across digital systems.Positioned as post-extractive trust infrastructure, the work outlines how the Coherence Ledger could support hiring, finance, media verification, and institutional risk analysis by making extraction visible and rewarding sustained coherent behavior over time.
This study examines the role of impact investing and climate finance in generating measurable social value through renewable energy projects by applying the Social Return on Investment (SROI) framework. Growing global investment in renewable energy has emphasized financial performance and emission reduction outcomes, while systematic measurement of social impacts remains limited. The purpose of this research is to assess how SROI can be used to quantify the social and environmental value created by renewable energy investments and to demonstrate its relevance for impact-oriented decision-making. A mixed-methods approach was employed, combining secondary project data analysis, stakeholder engagement, outcome mapping, and monetization of social and environmental benefits to calculate SROI ratios. The findings reveal that renewable energy projects consistently produce social returns exceeding the initial investment, with SROI ratios varying according to project type, scale, stakeholder involvement, and socio-economic context. Community-based and decentralized projects tend to generate higher relative social returns, driven by employment creation, improved energy access, health improvements, and environmental benefits. The study concludes that integrating SROI into climate finance evaluation enhances transparency, accountability, and alignment between financial objectives and sustainable development goals.
Abstract:The pervasive integration of digital technologies has fundamentally redefined the operational paradigms of commerce, finance, and accounting. This paper explores the multidimensional impact of Digital Transformation (DT) across these interconnected sectors, focusing on the adoption and efficacy of Artificial Intelligence (AI), Robotic Process Automation (RPA), and Blockchain technology. Through a systematic qualitative review of recent literature and industry frameworks, this study examines how traditional financial workflows are evolving into automated, data-driven ecosystems. The findings indicate that while DT significantly enhances real-time reporting, fraud detection, and transactional efficiency, organizations face substantial barriers, including high implementation costs, data security vulnerabilities, and a growing digital skills gap. The paper concludes that successful digital transformation requires not only technological investment but also a strategic realignment of organizational culture and regulatory compliance frameworks. Future research trajectories emphasize the need for standardized continuous auditing protocols and scalable decentralized finance (DeFi) architectures.
Blockchain and decentralized finance have revolutionized the financial ecosystem while simultaneously exposing it to cryptocurrency phishing attacks. Existing phishing detection methods primarily rely on graph learning, but they face significant limitations. Static graph learning approaches fail to account for the temporal evolution of phishing patterns, while semi-dynamic methods, such as those combining static GNNs with LSTM, struggle to capture the irregular and bursty nature of blockchain transactions. Moreover, these methods overlook the diversity of Ethereum transactions, treating them as homogeneous graphs, and heavily rely on supervised learning, which requires extensive labeled data that is not readily available. These limitations reduce their adaptability to emerging phishing threats. In this paper, we present PhishEye, a fully dynamic self-supervised system that monitors on-chain transactions to detect phishing activities. PhishEye formulates Ethereum transactions as a heterogeneous temporal attributed multi-graph and incorporates a novel temporal graph contrastive learning model, which captures both temporal patterns and heterogeneous transaction types. The evaluation on a dataset of 161,658 addresses and 416,541 transactions shows that PhishEye outperforms existing methods, achieving an F1 score of 87.23% and an AUC of 98.43% for phishing transaction detection, and an F1 score of 94.19% and an AUC of 98.03% for phishing account detection. In real-world deployment from May 1, 2023 to July 31, 2024, PhishEye identified 1,803 previously unknown phishing addresses, providing early alerts that helped prevent losses exceeding 2 billion USD.
The rapid advancement of blockchain technology has given rise to Decentralized Finance (DeFi), a financial ecosystem that operates without traditional intermediaries and challenges the foundational structures of conventional banking. DeFi platforms enable peer-to-peer financial services through smart contracts, offering increased transparency, accessibility, and efficiency. This study aims to analyze the potential of DeFi to disrupt traditional banking models by examining its core mechanisms, value propositions, and structural differences from centralized financial institutions. The research seeks to assess both the opportunities and challenges posed by DeFi in reshaping financial intermediation. A qualitative analytical approach was employed, drawing on an integrative review of peer-reviewed literature, industry reports, and documented DeFi case examples. Data were analyzed through thematic synthesis to compare DeFi functionalities with traditional banking operations, focusing on governance, risk management, and financial inclusion. The findings indicate that DeFi introduces innovative financial models that reduce transaction costs, expand access to financial services, and enhance operational transparency. The study concludes that DeFi represents a transformative yet complementary force rather than a complete replacement for traditional banking. Its future impact will depend on regulatory adaptation, technological maturity, and institutional integration.
Education endowment funds are increasingly promoted as sustainable financing instruments to support long-term educational development, particularly within decentralized governance systems. However, empirical evidence on how such funds are governed and implemented at the local level remains limited. This study examines the governance of the Education Endowment Fund in Bojonegoro Regency, Indonesia, focusing on the translation of policy intentions into institutional practices and school-level utilization. Drawing on qualitative data from in-depth interviews and policy document analysis, the study finds that although the fund operates within a formally structured governance framework, its implementation is characterized by centralized decision-making, compliance-oriented accountability mechanisms, and constrained local agency. Consequently, the fund is largely utilized to address short-term operational needs rather than to advance long-term sustainability objectives. The findings also reveal the importance of informal coordination and adaptive practices in navigating administrative complexity, albeit with uneven outcomes across institutions. This study contributes to debates on education financing governance by highlighting the critical role of local governance dynamics in shaping policy outcomes.
Pakistan's most significant federalist initiative, the 18th Constitutional Amendment (2010), scrapped the Concurrent Legislative List and transferred wide-ranging legislative, administrative, and fiscal responsibilities to the provinces. But more than ten years on, devolution remains uneven. In this paper, we explore the administrative, political and institutional obstacles to devolution between 2010 and 2018, with a focus on Centre-Punjab relations, the pivot of Pakistan's federation. Through a qualitative documentary analysis of parliamentary proceedings, archival documents, institutional reports and academic work, we argue that bureaucratic mediation operates as a two-pronged process: provincial bureaucracies, especially in Punjab, facilitate some devolved functions, while federal bureaucracies continue to exert control via regulatory coordination, conditional fiscal transfers and legal grey areas. The National Finance Commission (NFC) Award, which increased provincial transfers, has not ended fiscal dependence: the provinces receive 60-70% of their budget from the centre. The removal of the Concurrent Legislative List resulted in unequal sectoral outcomes - provincialization in health and education, but contested labour and interprovincial coordination. We suggest that constitutional devolution in the absence of simultaneous bureaucratic, fiscal autonomy and effective intergovernmental coordination creates a hybrid governance form: constitutionally decentralized and operationally centralised. In the case of Punjab, we find that bureaucratic capacity is not enough; path dependence, bureaucratic opposition and political bargaining over devolution shape the outcomes. Our insights enrich understanding of decentralization theory by identifying bureaucratic mediation as a critical variable and provide policy lessons for other federations in the midst of reforms. References Adeney, K. 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Rethinking decentralization in developing countries. World Bank. Mustafa, Z. (2019). The 18th Amendment and Pakistan's federal evolution. The Lahore Journal of Economics, 24(2), 1–28. Naseer, A., & Khalid, I. (2021). Bureaucratic mediation in Pakistan's devolution. Asian Journal of Political Science, 29(3), 301–320. https://doi.org/10.1080/02185377.2021.1967304 National Assembly of Pakistan. (2014). Parliamentary debates on devolution implementation. Government of Pakistan. National Finance Commission. (2009). 7th National Finance Commission Award 2009. Ministry of Finance, Government of Pakistan. Niskanen, W. A. (1971). Bureaucracy and representative government. Aldine-Atherton. North, D. C. (1990). Institutions, institutional change and economic performance. Cambridge University Press. Oates, W. E. (1999). An essay on fiscal federalism. Journal of Economic Literature, 37(3), 1120–1149. https://doi.org/10.1257/jel.37.3.1120 Organisation for Economic Co-operation and Development. 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Open access
South Asian Studies and Conflicts
Politics and Conflicts in Afghanistan, Pakistan, and Middle East
Mohd Saleem, Sohrab, Matloob Ullah Khan, Faizan Khan Sherwani
Key components of blockchain technology, DeFi represent a revolutionary advance in digital contracts and automated trades, and they are integrated into decentralized networks such as Ethereum. These self-executing contracts eliminate the need for middlemen by autonomously enforcing specified terms. This paper offers a thorough analysis of Decentralized Finance (DeFi), smart contracts, covering their underlying theories, technological foundations, wide range of applications, and ramifications in context of financial inclusion and investment. In order to clarify the workings and practical applications of such innovations, the research technique comprises a methodical evaluation of the literature, an examination of case studies, and an amalgamation of empirical data. This study evaluates their effects on efficiency, transparency, and trust in international transactions by looking at how they are revolutionizing industries like finance, and decentralized governance. It also thoroughly examines security considerations, including best practices and vulnerabilities, as well as regulatory issues and new developments.
Relevance. Problem statement. The rapid development of Decentralized Finance (DeFi) and the expansion of blockchain technologies within the digital economy and the broader process of financial digitalization complicate the application of traditional approaches to accounting and taxation of digital assets. The absence of clear criteria for interpreting the economic substance of DeFi and its implications for the recognition, measurement, and disclosure requirements of digital assets leads to heterogeneity in accounting practices, reduced comparability of financial reporting, and increased risks for auditors and investors. Consequently, there is a need to identify accounting-relevant characteristics of DeFi that can serve as a basis for accounting decisions regarding digital assets and for establishing a unified approach to their classification and measurement in accordance with International Financial Reporting Standards (IFRS). The purpose of the article is to provide a conceptual justification and structured generalization of the impact of DeFi and blockchain technologies on the methodology of accounting for digital assets through the identification of accounting-relevant characteristics that determine the specific features of their recognition, measurement, and disclosure in financial statements in accordance with IFRS, as well as their implications for the formation of tax liabilities within the DeFi environment. Methodology. The research objectives were addressed using general scientific and specialized methods, including analysis, synthesis, induction, deduction, comparison, abstraction, and a systems approach, which ensured an appropriate level of substantiation of the proposed arguments and the formulation of well-grounded conclusions. Results. The findings indicate that the transactional transparency of blockchain is accompanied by new valuation risks that affect asset measurement and revenue recognition. Existing tax regulations often fail to account for the specific characteristics of the DeFi ecosystem. Accounting-relevant characteristics of DeFi have been systematized, demonstrating that their influence extends beyond the accounting treatment of digital assets to the specific features of the protocol-based financial architecture within which economic rights and obligations are executed through algorithmic mechanisms without a centralized counterparty. Their systemic impact on the application of control criteria, the determination of the existence of contractual rights to claims, the selection of measurement models, the identification of the timing of revenue and liability recognition, and the scope of risk disclosures under IFRS has been substantiated. The theoretical contribution of the results lies in shifting from a descriptive analysis of blockchain technology to a structured accounting interpretation of DeFi from the perspective of control, measurement, and risk management concepts. Practical significance. The identification of accounting-relevant characteristics of DeFi is essential for developing a systematic approach to accounting for digital assets in a decentralized environment, as the protocol-based ecosystem of DeFi fundamentally alters the nature of the emergence of rights and obligations as well as the accrual of income, directly affecting the application of IFRS requirements. Such an approach ensures conceptual consistency between technological innovations and the regulatory framework of accounting and enhances the quality of financial information under conditions of financial system digitalization. The practical significance of the study lies in establishing a basis for updating corporate accounting policies and developing tax instruments that promote transparency and reduce risks in the digital asset sector. Prospects for further research. Future research should focus on improving disclosure standards and developing algorithmic models for the automated identification of economic transactions and tax events based on on-chain data.
Decentralized Finance (DeFi) offers open and permissionless financial services, but its core infrastructure remains exposed to serious security failures. Representative infrastructure classes such as decentralized exchanges (DEXs), protocols for loanable funds (PLFs), and cross-chain bridges matter because failures can propagate widely. This work presents a layered and empirically grounded framework for DeFi vulnerability prioritization. We analyze 558 exploit incidents from 2021–2025 and trace their mechanisms, vulnerabilities, and threat vectors across representative DeFi infrastructure classes. We introduce three complementary components: (1) a Risk Priority Number (RPN) used as an interpretable FMEA-style baseline for attack ranking, (2) an Adversarial Feasibility Score (AFS) that captures exploit feasibility from mapped adversarial-trait prevalence and accessibility, and (3) a Vulnerability-Centric Risk Score (VRS) defined as a structured priority ranking combining empirical likelihood, absolute economic severity, and attacker feasibility. The main validated model uses median per-incident USD loss as a consistent severity signal across the full incident dataset. Temporal validation shows that the structured vulnerability-priority model outperforms the multiplicative baseline and improves on the empirical base rank across both temporal holdouts and both future targets. The resulting framework provides an auditable remediation ordering for protocol developers, auditors, and risk managers.
Open access
Public-Private Partnership Projects
Infrastructure Resilience and Vulnerability Analysis
The development of small business at the regional level is one of the key factors ensuring sustainable economic growth, employment expansion, and reduction of territorial disparities. In emerging economies, particularly in Uzbekistan, small business entities play a significant role in generating income, stimulating entrepreneurial activity, and strengthening regional economic resilience. However, despite large-scale reforms aimed at supporting entrepreneurship, substantial differences remain among regions in terms of access to finance, infrastructure quality, market opportunities, and institutional efficiency.This article examines the economic mechanisms of small business development in the regions of Uzbekistan through a comparative analysis of international practices, including the experiences of the United States, Germany, and South Korea. The study applies comparative, statistical, institutional, and analytical methods to evaluate the effectiveness of financial-credit instruments, tax incentives, innovation infrastructure, and decentralized governance models.The findings demonstrate that successful regional small business development depends on the coordinated interaction of three major factors: effective financial mechanisms, adaptive institutional systems, and developed entrepreneurial infrastructure. The study identifies the main constraints in Uzbekistan, including centralized management, weak regional financial institutions, and uneven territorial development.Based on the results, several policy recommendations are proposed, including decentralization of support mechanisms, expansion of regional financing instruments, development of business incubators and technology parks, and implementation of differentiated regional entrepreneurship strategies. The practical significance of the study lies in developing proposals aimed at improving the competitiveness and sustainability of small business entities in the regions of Uzbekistan.