Wansen Wang, P. F. Zhang, Renjie Ji, Wenchao Huang · 8 authors
Some smart contracts violate decentralization principles by defining privileged accounts that manage other users' assets without permission, introducing centralized risks that have caused financial losses. Existing methods, however, face challenges in accurately detecting diverse centralized risks due to their dependence on predefined behavior patterns. In this paper, we propose JANUS, an automated analyzer for Solidity smart contracts that detects financial centralized risks independently of their specific behaviors. JANUS identifies differences between states reached by privileged and ordinary accounts, and analyzes whether these differences are finance-related. Focusing on the impact of risks rather than behaviors, JANUS achieves improved accuracy compared to existing tools and can uncover centralized risks with unknown patterns. To evaluate JANUS's performance, we compare it with other tools using a dataset of 540 contracts. Our evaluation demonstrates that JANUS outperforms representative tools in terms of detection accuracy for financial centralized risks. Additionally, we evaluate JANUS on a real-world dataset of 33,151 contracts, successfully identifying two types of risks that other tools fail to detect. We also prove that the state traversal method and variable summaries, which are used in JANUS to reduce the number of states to be compared, do not introduce false alarms or omissions in detection.
Hybrid Finance (HyFi) is a research and implementation initiative focused on establishing an operational framework that enables legally interpretable financial relationships to be settled using decentralized execution mechanisms. Historically, Traditional Finance (TradFi) and Decentralized Finance (DeFi) developed as mutually incompatible systems. TradFi ensures regulatory compliance, identity accountability, and institutional trust but suffers from latency and geographic constraints. DeFi enables transparent, borderless, and automated settlement but lacks enforceable responsibility mapping in real-world contractual contexts. The HyFi framework introduces a translation architecture that separates relationship governance from value execution. Institutional structures define responsibility and legal context, while decentralized networks perform settlement. A certification layer binds cryptographic execution to real-world intent, producing auditable and compliance-compatible financial records. This community archives research papers, technical disclosures, implementation references, diagrams, and supporting documentation related to: Hybrid financial operational models Compliance-aware blockchain settlement Certified digital asset transactions Programmable accountability frameworks Institutional adoption methodologies Educational and operational standards for blockchain integration The objective of this repository is to document the emergence of a third financial paradigm — not a replacement of TradFi or DeFi, but a structured convergence enabling borderless yet compliant financial activity.
Термин сферы децентрализованных финансов анализируется в рамках когнитивной парадигмы. Целью исследования является определение роли когнитивно-матричного анализа в контексте изучения терминов рассматриваемой области знания. Объектом исследования выступает термин “decentralized finance”. Предметом является применение когнитивно-матричного анализа как метода изучения терминолексики сферы децентрализованных финансов. Научная новизна исследования заключается в том, что впервые в отечественном терминоведении проводится изучение англоязычных терминов указанной сферы с когнитивной позиции. В частности, приводится пример использования когнитивно-матричного анализа для определения концептуальной структуры термина изучаемой области знания. В статье рассматривается несколько подходов к определению понятия «термин»: субстанциональный, функциональный и когнитивный. Проводится когнитивно-матричный анализ на материале термина “decentralized finance” и его определений, закрепленных в глоссариях децентрализованных платформ, приложений и новостных англоязычных интернет-ресурсов, таких как Binance Academy, Consensys, Ethereum Website, Ethereum Glossary и Tastycrypto. В результате анализа определено, что наибольшую компонентную представленность в структуре концепта DECENTRALIZED FINANCE демонстрируют «техническая и технологическая» и «социальная» области, в то время как «финансовая» и «правовая» репрезентированы менее широко, что обусловлено смещением акцента в определениях термина с базовых характеристик на инновационные и дифференцирующие. Когнитивно-матричный анализ позволяет выявлять периферийные области и концептуальные компоненты когнитивной структуры терминов сферы децентрализованных финансов, подчеркивая их междисциплинарный характер. The term “decentralized finance” is analyzed within the framework of the cognitive paradigm. The article examinesthe application of cognitive-matrix analysis as a method for studying the terminological vocabulary of the specified domain. The object of the research is the term “decentralized finance”, while the subject is the application of cognitive matrix analysis as a method for studying the terminological vocabulary of decentralized finance. The novelty of the research lies in the fact that, for the first time in Russian terminology studies, English-language terms of the specified field are examined from a cognitive perspective. An example is provided of how cognitive matrix analysis can be used to identify the conceptual structure of decentralized finance terms. The article considers several approaches to defining the concept of the term: the substantial, functional, and cognitive. A cognitive matrix analysis is conducted on the material of the term “decentralized finance”, as represented in the glossaries of decentralized platforms, applications, and English-language news resources such as Binance Academy, Consensys, Ethereum Website, Ethereum Glossary, and Tastycrypto. The analysis reveals that the “technical and technological” and “social” peripheral domains are most prominently represented in the structure of the concept DECENTRALIZED FINANCE, whereas the “financial” and “legal” domains are less explicitly present. This is due to the shift in focus from basic characteristics of the concept to innovative and differentiating features in the term’s definitions. Cognitive matrix analysis makes it possible to identify peripheral domains and conceptual components of the cognitive structure of DeFi terminological vocabulary, highlighting its interdisciplinary nature.
Omar M. Bawazeer, Md Mahfuzur Rahman, Mohammad Hammoudeh
Smart contracts (SC) are deployed on blockchain platforms without sufficient descriptive metadata. This lack of metadata significantly limits their discoverability, making it challenging for consumers to identify and select suitable contracts. This paper presents a comparative analysis of existing smart contract registry design approaches. It first identifies the core design properties of smart contract registries, such as descriptive metadata, description format, registry type, structure, platform scope, and discovery mechanism, and uses these dimensions as the foundation for our analysis. Drawing from this analysis, we propose a two-part taxonomy that distinguishes between purpose-based and business-based designs. We then analyze representative smart contract registry designs and highlight current key challenges in the field. By mapping the strengths, limitations, and trade-offs of these designs, this paper provides a reference to guide developers and platform architects. It aims to support the design of more efficient, transparent, interoperable, and decentralized smart contract registries, ultimately improving contract discoverability and selection for consumers.
Ethereum-Smart Contracts verwalten häufig erhebliche finanzielle Werte. Da sie praktisch unveränderlich sind und häufig böswilligen Akteuren ausgesetzt sind, die durch finanziellen Gewinn motiviert sind, stellt die semantische Korrektheit eine zentrale Sicherheitsanforderung dar. Etablierte Testmethoden reichen oft nicht aus, um die Korrektheit über alle möglichen Ausführungspfade hinweg zu gewährleisten. Daher stellt die formale Verifikation ein wesentliches Mittel dar, um solche Sicherheitsgarantien zu stärken. Diese Arbeit untersucht die auf symbolischer Ausführung basierende Verifikation von Ethereum-Smart-Contracts unter Verwendung des KEVM-Frameworks sowie zweier darauf aufbauender Werkzeuge auf höherer Abstraktionsebene: ACT und Kontrol. Diese Arbeit behandelt Fragestellungen hinsichtlich der Ausdrucksstärke und Konstruktion von Beweisen sowie der Nutzbarkeit und Interpretierbarkeit sowohl von Beweisdefinitionen als auch von generierten Beweisartefakten. Es wird untersucht, ob und welche praktischen Herausforderungen bei der Verwendung von KEVM und zugehörigen Werkzeugen auftreten, einschließlich der Syntax, der verfügbaren Debugging-Werkzeuge sowie der Analyse von Beweisen und Gegenbeweisen. Anschließend erfolgt eine Evaluierung, wie semantische Eigenschaften über alle Werkzeuge hinweg spezifiziert werden können und wie präzise diese spezifiziert werden, wobei insbesondere die Zielkonflikte zwischen unterschiedlichen Abstraktionsebenen hervorgehoben werden. Darüber hinaus verifizieren wir semantische Eigenschaften von ERC20-Token-Smart-Contracts mit besonderem Fokus darauf, ob bestimmte Einträge in der Common Vulnerabilities and Exposures (CVE)-Datenbank tatsächlich korrekt sind oder mithilfe von KEVM widerlegt werden können. Zu diesem Zweck analysieren wir die gemeldete Schwachstelle, formulieren ein formales Argument gegen die behauptete Verletzung und konstruieren darauf aufbauend einen Beweis unter Verwendung von Kontrol. Dabei zeigen wir, wie semantische Eigenschaften innerhalb des Frameworks formuliert und verifiziert werden können. Abschließend untersuchen wir die Community-Aktivität rund um KEVM und dessen Ökosystem. Dazu werden GitHub-Repository-Metriken sowie Kommunikationsdaten aus Discord ausgewertet, um Entwicklungsaktivität, Dynamiken der Beitragenden sowie Muster im Nutzer-Support zu analysieren. Diese kombinierte Perspektive aus technischer und empirischer Sicht liefert eine ganzheitliche Betrachtung von KEVM sowohl als formales Verifikationsframework als auch als Entwickler-Ökosystem.
Perkembangan teknologi digital telah mentransformasi praktik akuntansi secara fundamental, memperluas perannya dari sekadar sistem pencatatan dan pelaporan menjadi instrumen strategis dalam pengambilan keputusan keuangan. Seiring dengan meningkatnya volume dan kompleksitas literatur mengenai akuntansi digital, diperlukan pemetaan sistematis untuk memahami struktur intelektual, tema penelitian utama, serta arah perkembangan bidang ini. Studi ini bertujuan untuk memetakan lanskap penelitian digital accounting dalam financial decision making menggunakan pendekatan bibliometrik. Data penelitian diperoleh dari publikasi terindeks Scopus dan dianalisis menggunakan teknik pemetaan bibliometrik melalui analisis kemunculan bersama kata kunci, jejaring penulis, institusi, dan negara. Hasil analisis menunjukkan bahwa decision making merupakan tema sentral yang menghubungkan berbagai klaster penelitian, dengan fondasi kuat pada sistem informasi akuntansi dan manajemen informasi. Selain itu, terdapat pergeseran signifikan menuju topik-topik mutakhir seperti artificial intelligence, machine learning, blockchain, automation, dan decentralized finance, yang menandai transformasi akuntansi digital menuju sistem prediktif dan real-time. Analisis kolaborasi juga mengungkap sifat global dan multidisipliner dari penelitian ini, meskipun beberapa tema seperti keberlanjutan dan teknologi emerging masih relatif kurang dieksplorasi. Temuan studi ini memberikan kontribusi konseptual dengan menyajikan gambaran komprehensif evolusi riset digital accounting serta memberikan implikasi praktis dan agenda riset masa depan bagi akademisi dan praktisi dalam mendukung pengambilan keputusan keuangan yang lebih efektif di era digital.
Financial Generative Pre-trained Transformers (FinGPT) with multimodal capabilities are now being increasingly adopted in various financial applications. However, due to the intellectual property of model weights and the copyright of training corpus and benchmarking questions, verifying the legitimacy of GPT's model weights and the credibility of model outputs is a pressing challenge. In this paper, we introduce a novel zkFinGPT scheme that applies zero-knowledge proofs (ZKPs) to high-value financial use cases, enabling verification while protecting data privacy. We describe how zkFinGPT will be applied to three financial use cases. Our experiments on two existing packages reveal that zkFinGPT introduces substantial computational overhead that hinders its real-world adoption. E.g., for LLama3-8B model, it generates a commitment file of $7.97$MB using $531$ seconds, and takes $620$ seconds to prove and $2.36$ seconds to verify.
Blockchain technology and smart contracts have revolutionized the way financial transactions are conducted in virtual environments. This review paper provides a comprehensive overview of the role of blockchain technology and smart contracts in shaping the future of virtual financial transactions. We explore the fundamentals of blockchain technology, its applications in the financial industry, and the pivotal role that smart contracts play in automating and securing virtual financial transactions. Furthermore, we discuss the benefits, challenges, and prospects of these innovations within the virtual financial landscape.
Financial transactions demand exceptionally robust security, especially in light of the rapid advancement of quantum computing, which poses a severe threat to classical cryptographic mechanisms used in modern banking systems. Among various financial operations, transaction processing remains the most critical and vulnerable component. To address this emerging challenge, we introduce a Distributed Ledger Technology (DLT)-based secure framework for quantum-resistant financial transactions. The proposed architecture leverages lattice-based cryptographic security to ensure resilience against quantum attacks while preserving essential security attributes such as privacy, accountability, and data integrity. Furthermore, to demonstrate its effectiveness, the proposed framework is also compared with existing solutions in the literature.
Purpose The absence of cryptocurrency (CC) tax regulations in many countries raises concerns about compliance and potential revenue losses. Understanding the factors that drive CC holders’ tax propensity is crucial for developing effective tax policies. Therefore, this research aims to explore the influence of contextual factors, e.g. CC legitimacy, CC investment risks, and social responsibility, and individual factors, e.g. attitude towards CC tax payment, technological competence and CC financial literacy, on CC tax payment propensity. Additionally, the study delves into the moderating role of financial literacy in the proposed model. Design/methodology/approach An integrated model of TPB-STC (theory of planned behaviour and social cognitive theory) was grounded in this study. Data were collected using a cross-sectional research approach through an online survey responded by CC investors. Findings The study found that attitude towards CC tax payment, social responsibility, legitimacy and CC financial literacy exerted a positive effect on the propensity to pay tax on CC. However, CC investment risks demonstrated a negative effect on propensity. Interestingly, the CC financial literacy-moderated interactions of crypto assets' legitimacy, technological competence and investment risks on CC tax payment propensity were significant. Practical implications The discoveries that emerged from this study contain practical and actionable insights for stakeholders, including regulators, tax authorities and investors. Educational programs focused on enhancing CC financial literacy should be integrated into public finance initiatives to improve taxpayers’ understanding of crypto taxation. Additionally, regulatory bodies can collaborate with crypto exchanges to implement transparent reporting mechanisms, making tax compliance more accessible and straightforward for investors. These actionable steps can help foster a proactive tax-paying culture, even in the absence of formal tax regulations. Originality/value This study provides a theoretical foundation of tax practices behaviour related to crypto in decentralized financial markets, paving the way for future research on self-regulating mechanisms within the present-day fast-moving crypto market.
On April 1, 2025 Circle Internet Group, Inc. (hereinafter referred to as "Circle," "the Company," or "issuer", filed a registration statement on Form S-1 with the U.S. Securities and Exchange Commission (SEC) contemplating the "offering [of]… shares of Class A common stock." After the additional filing of prospectus amendments, the final offering prospectus is dated August 12, 2025. The offering of 34,000,000 shares was priced before market opening on June 4, 2025 at $31 per share. Circle's disclosure documents provide an excellent description of the many new blockchain-enabled Decentralized Finance [DeFi] technological and operational challenges facing participants and investors. These valuable disclosures benefit all who seek to understand these important developments impacting the future stability of global financial and currency markets. It is the actual disclosure language of Circle Internet Group, Inc. in their prospectus that is the focus of the article.
The rapid growth of blockchain technology has driven the widespread adoption of smart contracts; however, their inherent vulnerabilities have led to significant financial losses. Traditional auditing methods, while essential, struggle to keep pace with the increasing complexity and scale of smart contracts. Large language models (LLMs) offer promising capabilities for automating vulnerability detection, but their adoption is often limited by high computational costs. Although prior work has explored leveraging large models through agents or workflows, relatively little attention has been given to improving the performance of smaller, fine-tuned models—a critical factor for achieving both efficiency and data privacy. In this paper, we introduce HKT-SmartAudit, a framework for developing lightweight models optimized for smart contract auditing. It features a multi-stage knowledge distillation pipeline that integrates classical distillation, external domain knowledge, and reward-guided learning to transfer high-quality insights from large teacher models. A single-task learning strategy is employed to train compact student models that maintain high accuracy and robustness while significantly reducing computational overhead. Experimental results show that our distilled models outperform both commercial tools and larger models in detecting complex vulnerabilities and logical flaws, offering a practical, secure, and scalable solution for smart contract auditing. The source code is available in the GitHub repository1.
The XRP Ledger sustains federated consensus without paying validators any protocol-level monetary reward: transaction costs are destroyed rather than distributed. This paper argues that the curatorship of the default Unique Node List (dUNL) functions as the economic mechanism that monetary rewards would otherwise provide, and develops a formal framework for evaluating its design. The central thesis is that RPCA security requires alignment across three independent layers-technical consensus, individual incentive constraints, and governance compositionand that the failure of any single layer undermines the other two. Three formal contributions support this claim. First, we introduce Bayesian action-incentive compatibility (BAIC), an equilibrium concept appropriate for consensus settings with discrete hidden actions and imperfect public monitoring, in which validators choose actions rather than reporting types and the curator cannot deploy monetary transfers. Closed-form Bellman values and local comparative statics characterise when honest dUNL participation is individually sustainable; in particular, operational cost is neutral for the honesty margin and binds only at the participation constraint. Second, we correct the coalition-security analysis by distinguishing economically viable from threshold-exceeding coalitions: an economic-security gap exists only when the maximum bribeable coalition size reaches the minimum stylised thresholdexceeding size, with the precise characterisation depending on the internal-allocation rule (equal sharing versus transferable bribes). Third, a triple-alignment theorem integrates these results and yields an archetype-conditional dUNL composition diagnostic. A scenario-based calibration using public XRPL Negative UNL data classifies the 35 dUNL validators by incentive archetype and computes G crit k for each type; the H archetype anchors the lowest economic-security margin but is too few in number for a homogeneous threshold-size coalition, so under the transferable-bribe convention the least-cost threshold coalition is heterogeneous, mixing H-type and I-type validators.
Double-entry bookkeeping ensures internal balance but offers limited independent evidence that reported state follows from complete, unaltered records under a stated accounting policy. Ian Grigg's operational triple-entry model—cryptographically linked inter-firm receipts—and subsequent advances in hash commitments, zero-knowledge proofs, and payment-layer compliance attestations motivate ledger-native assurance: verification artifacts produced during accounting close, not assembled from exports afterward. This working paper presents a design-science framework with four assurance layers (source, posting, record, disclosure); a taxonomy of source-anchoring paths including on-chain settlement, TLS-attested ingestion, and bilateral finalization; an analysis of payment-layer versus ledger-layer zero-knowledge statements; and a close-cadence model distinguishing continuous, partial, and batch close under different capture postures. We state explicit scope limits aligned with audit evidence theory and outline an empirical and regulatory research agenda.
The rapid growth of entities that hold, trade and earn revenue from crypto-assets has outpaced the development of auditing guidance tailored to this environment. Digital assets have moved decisively from the margins of finance into the balance sheets of regulated funds, market makers, fintechs and conventional corporates, with the global crypto-asset market now measured in the trillions of dollars. Auditors are now routinely asked to express opinions on financial statements that include digital assets, yet the established toolkit of external confirmations, period-end cutoff procedures and observable market prices maps poorly onto blockchain-based holdings and continuous, automated trading. This paper sets out, from a practitioner's standpoint, the principal challenges encountered when auditing crypto-holding and trading entities: establishing the existence and ownership of on-chain assets; obtaining assurance over the completeness of an entity's wallet population; valuing illiquid tokens, liquidity-pool positions, non-fungible tokens and stablecoins; auditing emerging instruments such as token loan agreements, warrants and forfeitures; addressing cutoff in markets that never close; and testing revenue arising from market-making, arbitrage and staking. For each area, the paper describes how the profession currently adapts existing standards-notably ISA 500, ISA 501, ISA 540 (Revised), ISA 240, IFRS 13 and the recently effective FASB ASC 350-60-and where meaningful gaps remain. The paper argues that strengthening audit practice in this domain is not a narrow technical concern but a matter of investor protection and financial-system integrity, given the scale of value now held in digital form and the heightened fraud and money-laundering risks that accompany it. It concludes with practical considerations for auditors and a call for more specific standard-setting and practitioner guidance.
This study aimed to develop a conceptual model for pricing digital assets by integrating behavioral finance perspectives and identifying psychological and social factors influencing investors’ decision-making in decentralized markets. A qualitative grounded theory approach was adopted. The study involved 15 experts in digital currencies, blockchain, and behavioral finance selected through purposive sampling until theoretical saturation was achieved. Data were collected via semi-structured interviews and textual content analysis. Open, axial, and selective coding were applied to build the theoretical framework. Reliability was confirmed using quality control indices such as Krippendorff’s alpha, Holsti coefficient, Scott’s Pi, and Cohen’s Kappa, all indicating high inter-coder agreement. The resulting model captured multiple determinants of digital asset pricing. Causal factors included emotional and psychological behaviors (e.g., fear of missing out, fear and greed), the influence of news and media, and social association effects. Contextual factors encompassed uncertainty, ambiguity, and market volatility. Strategic factors such as market trust and credibility, investors’ knowledge and awareness, and reference points were identified. Core conditions included regulatory and legal environments, technological infrastructure, and macroeconomic conditions. Consequences involved enhanced market transparency, analysts’ and advisors’ influence, institutional and retail investor interactions, and the impact of past experiences on risk-taking. The proposed behavioral finance-driven model demonstrates that digital asset pricing extends beyond classical economic frameworks, heavily shaped by investor psychology and external information dynamics. The findings can guide investors toward more rational strategies and support policymakers in creating effective regulations and safer decentralized financial ecosystems.
The accounting for cryptoassets under current IFRS remains fragmented. Following the IFRS Interpretations Committee's 2019 agenda decision on holdings of cryptocurrencies, most holders default to IAS 38 Intangible Assets unless IAS 2 Inventories applies. That outcome produces incomplete comparability, weak performance reporting, and a recurring tension between the economic liquidity of many cryptoassets and the accounting model applied to them. This discussion paper proposes a narrow holder-side framework for fungible cryptoassets that do not provide the holder with an enforceable claim on an issuer, measured subsequently at fair value through profit or loss, with business model affecting presentation and disclosures rather than measurement. The analysis also addresses matters commonly omitted in early crypto accounting proposals: counterpart entries for acquisition, use, rewards and disposal; liability-side consequences arising from taxes, slashing, safeguarding, financing and legal obligations; interaction with IFRS 13, IAS 12, IAS 37 and IFRS 7; and practical illustrations across treasury entities, funds, exchanges, validators, Web3 operators and payment platforms. Public-company reporting examples are incorporated as illustrative evidence of how existing accounting frameworks affect balance-sheet presentation, profit or loss, deferred taxes and scope boundaries in practice.
The accounting for cryptoassets under current IFRS remains fragmented. Following the IFRS Interpretations Committee's 2019 agenda decision on holdings of cryptocurrencies, most holders default to IAS 38 Intangible Assets unless IAS 2 Inventories applies. That outcome produces incomplete comparability, weak performance reporting, and a recurring tension between the economic liquidity of many cryptoassets and the accounting model applied to them. This discussion paper proposes a narrow holder-side framework for fungible cryptoassets that do not provide the holder with an enforceable claim on an issuer, measured subsequently at fair value through profit or loss, with business model affecting presentation and disclosures rather than measurement. The analysis also addresses matters commonly omitted in early crypto accounting proposals: counterpart entries for acquisition, use, rewards and disposal; liability-side consequences arising from taxes, slashing, safeguarding, financing and legal obligations; interaction with IFRS 13, IAS 12, IAS 37 and IFRS 7; and practical illustrations across treasury entities, funds, exchanges, validators, Web3 operators and payment platforms. Public-company reporting examples are incorporated as illustrative evidence of how existing accounting frameworks affect balance-sheet presentation, profit or loss, deferred taxes and scope boundaries in practice.