Blockchain Papers

CY, Topo Labs

The user-ownership model of Web3 commerce is widely viewed as a potential paradigm shift for the digital economy, yet its macroeconomic implications remain under-quantified within a unified, dynamic, and parameterized framework. This paper develops a tractable dynamic macroeconomic model of a “wealth flywheel” featuring two feedback channels. The income loop operates through profit-backed user rebates that raise income-equivalent purchasing capacity and stimulate consumption. The asset loop operates through consumption-driven profit and valuation growth, which expands household wealth under user ownership and feeds back into consumption via wealth effects. In a static setting, the paper derives a closed-form consumption multiplier and a corresponding stability condition. Aggregate consumption responds proportionally to an exogenous income impulse, and the system is stable if the combined strength of rebate-induced consumption feedback and wealth-effect amplification remains below unity. The static mechanism is then embedded into a global multi-period simulation framework with time-varying Web3 penetration, finite-horizon household deposit reallocation into consumption, and endogenous valuation paths. Using illustrative parameterizations, the paper simulates trajectories for global real GDP, equity market capitalization, household wealth, and inflation under neutral and aggressive adoption scenarios. The analysis further examines distributional implications when capitalization gains are directed toward user cohorts with higher marginal propensities to consume. The framework provides a parsimonious diagnostic for stability in mechanism design and contributes to macro-prudential discussions of self-reinforcing growth dynamics. Importantly, the analysis abstracts from collateralized borrowing, leverage, rehypothecation, and other financial intermediation channels. All amplification effects in the model arise from ownership structure and wealth effects rather than from credit-driven financial accelerators.

Yihan Hong, Hengxiang Feng, Yinghan Wang, Boxuan Li

The approval of the Bitcoin Spot ETF in January 2024 marked a transformative event in cryptocurrency markets, signaling increased institutional adoption and integration into traditional finance. This study examines Bitcoin's changing relationships with traditional assets, including equities, gold, and fiat currencies, following this milestone. Using rolling correlation analysis, Chow tests, and DCC-GARCH models, we found that Bitcoin's correlation with the S\&P 500 increased significantly post-ETF approval, indicating stronger alignment with equities. Its relationship with gold stabilized near zero, while its correlation with the U.S. Dollar Index remained consistently negative, reflecting its continued independence from fiat currencies. These findings offer insights into Bitcoin's evolving role in portfolios, implications for market stability, and future research opportunities on cryptocurrency integration into traditional financial systems.

Animesh Mishra

Decentralized federated learning (DFL) enables collaborative model training without centralized trust, but it remains vulnerable to Byzantine clients that poison gradients under heterogeneous (Non-IID) data. Existing defenses face a scalability trilemma: distance-based filtering (e.g., Krum) can reject legitimate Non-IID updates, geometric-median methods incur prohibitive $O(n^2 d)$ cost, and many certified defenses are evaluated only on models below 100M parameters. We propose Spectral Sentinel, a Byzantine detection and aggregation framework that leverages a random-matrix-theoretic signature: honest Non-IID gradients produce covariance eigenspectra whose bulk follows the Marchenko-Pastur law, while Byzantine perturbations induce detectable tail anomalies. Our algorithm combines Frequent Directions sketching with data-dependent MP tracking, enabling detection on models up to 1.5B parameters using $O(k^2)$ memory with $k \ll d$. Under a $(σ,f)$ threat model with coordinate-wise honest variance bounded by $σ^2$ and $f < 1/2$ adversaries, we prove $(ε,δ)$-Byzantine resilience with convergence rate $O(σf / \sqrt{T} + f^2 / T)$, and we provide a matching information-theoretic lower bound $Ω(σf / \sqrt{T})$, establishing minimax optimality. We implement the full system with blockchain integration on Polygon networks and validate it across 144 attack-aggregator configurations, achieving 78.4 percent average accuracy versus 48-63 percent for baseline methods.

Erdhi Widyarto Nugroho, R. Rizal Isnanto, Luhur Bayuaji

The Federated Byzantine Agreement (FBA) achieves rapid consensus by relying on overlapping quorum slices. But this architecture leads to a high dependence on the availability of validators when about one fourth of validators go down, the classical FBA can lose liveness or fail to reach agreement. We thus come up with an Adaptive FBA architecture that can reconfigure quorum slices intelligently based on real time validator reputation to overcome this drawback. Our model includes trust scores computed from EigenTrust and a sliding window behavioral assessment to determine the reliability of validators. We have built the intelligent adaptive FBA model and conducted tests in a Stellar based setting. Results of real life experiments reveal that the system is stable enough to keep consensus when more than half of the validators (up to 62 percent) are disconnected, which is a great extension of the failure threshold of a classical FBA. A fallback mode allows the network to be functional with as few as three validators, thus showing a significant robustness enhancement. Besides, a comparative study with the existing consensus protocols shows that Adaptive FBA can be an excellent choice for the next generation of blockchain systems, especially for constructing a resilient blockchain infrastructure.

Meza Pinto, Hugo Eduardo

Este boletim quinzenal gratuito visa analisar o comportamento do Bitcoin, um ativo financeiro digital, oferecendo notícias, análises gráficas e informações sobre as mais recentes novidades, softwares e aplicativos relacionados a essa criptomoeda. Nosso objetivo é enriquecer as discussões em torno da cultura do Bitcoin, colaborando com a Amauta, uma instituição de economia criativa que busca disseminar conhecimento sobre inovação, educação e finanças na comunidade acadêmica e empresarial. Esperamos que este trabalho represente uma contribuição valiosa para o debate. Reconhecemos a importância do Bitcoin e seu impacto na economia global, motivo pelo qual nos dedicamos a fornecer informações atualizadas aos nossos leitores. Acreditamos que ao promover discussões e compreensão sobre o Bitcoin, podemos incentivar a adoção e o uso responsável dessa tecnologia disruptiva. Para além das análises e informações sobre o Bitcoin, incentivamos ativamente nossos leitores a se educarem sobre finanças pessoais e investimentos. Acreditamos que, munidos do conhecimento adequado, todos podem tomar decisões financeiras inteligentes e bem informadas. Comprometemo-nos a fornecer informações de alta qualidade e precisas, esforçando-nos para manter nossos leitores atualizados sobre as últimas tendências e desenvolvimentos no mundo do Bitcoin. Esperamos que este relatório seja do seu agrado e contribua para uma compreensão mais aprofundada do Bitcoin e das finanças pessoais em geral.

MAZARI, Ilyes Tarik, Mazari, Yanis, Ilyan, Mazari

We present the Y.I.N. Mazari Architecture, an 8-pillar privacy-preserving federated learning system built around a novel cryptographic ordering: DP→ZK→HE (Differential Privacy →Zero-Knowledge Proof →Homomorphic Encryption) applied to federated learning gradients. The name Y.I.N. honors Yanis, Ilyan, and Neylia Mazari, while embodying the core principle that Your Information Never leaves your control.We identify a fundamental barrier in privacy-preserving federated learning: the inability to verify that participants correctly applied differential privacy noise while maintainin computational efficiency. The Y.I.N. Mazari Ordering resolves this barrier through a specific sequencing of cryptographic operations.This paper extends the classical architecture into the quantum domain through the QFED-MAZARI system,introducing the Mazari Quantum Ordering: QDP→MUA→DQEM(Quantum Differential Privacy →Manifold Unitary Aggregation →Distributed Quantum Error Mitigation). Experimental results demonstrate 99.37% model accuracy with 223× speed improvement in classical systems, while the quantum extension achieves 91.9% accuracy with 40–50% communication reduction. Together, the classical and quantum architectures establish a comprehensive 30-year intellectual property runway.

Petronela Alice Grigorescu, Alexandru Cătălin Neagu, Cătălin Alexandru, Marius Dan Coman

In an era of rising digitalization, terms focused on blockchain, smart contracts, and artificial intelligence are becoming increasingly prominent both theoretically and practically in financial markets and implicitly in the performance of businesses. Considered the second blockchain in the world, smart contracts are designed to automate the agreement between the contract creator and recipient in a time-efficient manner for both participants. The purpose of this article is to present the benefits of using smart contracts in blockchain applications. The research methodology will thus involve a qualitative analysis of specialized publications, specifically a review that examines the effects of using smart contracts from 2015 to 2024. The results obtained from the research illustrate the benefits generated by using this type of blockchain and build support for professionals as well as for companies.

Wanli Liu, Jianlin Li, Na Chen

Accounting is undergoing a radical transformation due to the integration of traditional information systems with blockchain technology and artificial intelligence. Openness, automation, and smart decision-making will all become a reality via this connection. However, traditional SAIS are typically centralized and do not inherently include blockchain or AI. In this study, Smart Accounting Information System (SAIS) technologies are redefined through the integration of these technologies to enhance transparency, automation, and real-time assurance. Blockchain technology's immutability, traceability, and AI's ability to recognize abnormalities and predict provide a more intelligent and secure auditing process. Conventional accounting methods have several issues, including delayed audits, lack of transparency, fraud, and human mistakes. Existing systems fail to provide intelligent anomaly detection and real-time transaction traceability. Financial reporting and audits need immutable records and proactive analytics. There is an urgent need for a single framework to ensure this requirement and its quick implementation. This study proposes the collaborative blockchain-AI audit trails method (CBAATM) for Smart Accounting Information Systems. This is done due to the difficulties mentioned. AI-powered modules utilize fuzzy inference to dynamically analyze audit risks and Random Forest classifiers to detect real-time fraud. This research project utilizes zero-knowledge proofs and homomorphic encryption to simultaneously handle data aggregation, privacy, and independent audits. Using middleware application programming interfaces makes integration with ERP and AIS systems easy. Throughout the testing process, the model outperforms conventional audits. The methodology, according to statistical research, ensures the detection accuracy ratio of 95%, integrity of the blockchain 99.2% of the time, identifies abnormalities 94.1% of the time, satisfies compliance standards 95.4% of the time, and reduces audit latency by 41.5% compared to other existing models.

Miels, Kareen

Inter-local cooperation (ILC) has long served as a pragmatic governance response in the Philippines, enabling local government units (LGUs) to address policy challenges that transcend administrative boundaries. Yet national experience under Section 33 of the 1991 Local Government Code shows that cooperation has often remained voluntary, procedurally thin, and dependent on Memoranda of Agreement rather than on institutionalized legal personality, pooled fiscal authority, and durable governance systems (Republic of the Philippines 1991; DILG, NEDA, and GIZ 2010; Miels and Mayer 2025). This article examines the Bangsamoro Autonomous Region in Muslim Mindanao (BARMM) as a case of subnational legal innovation following the enactment of the Bangsamoro Local Governance Code (BLGC) in 2023 (BAA 49, 2023). Drawing on documentary analysis and national ILC experience, the study analyzes how the BLGC reconfigures statutory authority for inter‑LGU cooperation and why BLGC‑aligned institutions have not yet consolidated in routine practice. The findings show that the BLGC provides one of the most explicit statutory foundations to date for horizontal cooperation – authorizing joint organizations, shared authority, and multi‑stakeholder participation – yet inter‑local cooperation in BARMM remains largely MOA‑based at present, reflecting an early, pre‑institutionalization stage (BAA 49, 2023; Miels and Mayer 2025). Interpreting this as reform sequencing rather than policy failure, the article demonstrates that rules‑in‑form are in place while the rules‑in‑use required for implementation – procedural clarity, pooled fiscal systems, organizational capacity, and integration into regional governance – are still being developed (Ostrom 1990; Pierson 2000; Mahoney and Thelen 2010). In doing so, the study reframes early implementation gaps as expected features of institutional transition and highlights the BLGC’s broader contribution to modernizing the legal foundations of inter‑local cooperation beyond Section 33, offering insights relevant to decentralization reform and intergovernmental governance in the Philippines.

Multazam, Mochammad Tanzil

Materi Crypto Assets dalam Decentralized Finance (DeFi) ini disampaikan dalam Rapat Pleno Majelis Tarjih dan Tajdid Pimpinan Pusat Muhammadiyah yang diselenggarakan di Yogyakarta pada 14 Desember 2025. Paparan ini bertujuan memberikan landasan konseptual dan analitis yang jernih mengenai aset kripto dalam perspektif teknologi, ekonomi, dan hukum, sebagai bahan pertimbangan ilmiah dalam proses tarjih dan ijtihad institusional. Pembahasan difokuskan pada klarifikasi kedudukan aset kripto sebagai aset digital, bukan sebagai alat pembayaran yang diterbitkan negara, serta penjelasan mengenai mekanisme kerja blockchain dan smart contract sebagai fondasi utama ekosistem DeFi. Materi ini menyoroti bagaimana aset kripto memperoleh nilai dari fungsi, manfaat, kelangkaan, dan kepercayaan pengguna, sekaligus membedakannya dari praktik spekulatif murni yang tidak memiliki underlying value. Selain itu, disampaikan pula pemetaan jenis-jenis aset kripto—termasuk cryptocurrency, stablecoin, utility token, security token, governance token, NFT, dan Real World Asset (RWA) token—beserta contoh penerapan nyatanya dalam sektor keuangan, industri kreatif, dan layanan publik. Paparan ini juga mengkaji risiko inheren aset kripto, seperti volatilitas, risiko teknologi, dan potensi penyalahgunaan, sehingga menegaskan pentingnya prinsip kehati-hatian, literasi, dan tata kelola. Materi ini mengaitkan perkembangan aset kripto dengan kerangka regulasi nasional, khususnya Peraturan Otoritas Jasa Keuangan Nomor 27 Tahun 2024, untuk menunjukkan bahwa aset kripto telah berada dalam rezim pengaturan resmi. Dengan demikian, materi ini diharapkan menjadi rujukan objektif dan proporsional bagi Majelis Tarjih dan Tajdid dalam merumuskan sikap, pandangan keagamaan, dan rekomendasi kebijakan yang berbasis ilmu pengetahuan serta kemaslahatan umat.

Lily Erickson

With the advent of machine learning and quantum computing, the 21st century has gone from a place of relative algorithmic security, to one of speculative unease and possibly, cyber catastrophe. Modern algorithms like Elliptic Curve Cryptography (ECC) are the bastion of current cryptographic security protocols that form the backbone of consumer protection ranging from Hypertext Transfer Protocol Secure (HTTPS) in the modern internet browser, to cryptographic financial instruments like Bitcoin. And there's been very little work put into testing the strength of these ciphers. Practically the only study that I could find was on side-channel recognition, a joint paper from the University of Milan, Italy and King's College, London\cite{battistello2025ecc}. These algorithms are already considered bulletproof by many consumers, but exploits already exist for them, and with computing power and distributed, federated compute on the rise, it's only a matter of time before these current bastions fade away into obscurity, and it's on all of us to stand up when we notice something is amiss, lest we see such passages claim victims in that process. In this paper, we seek to explore the use of modern language model architecture in cracking the association between a known public key, and its associated private key, by intuitively learning to reverse engineer the public keypair generation process, effectively solving the curve. Additonally, we attempt to ascertain modern machine learning's ability to memorize public-private secp256r1 keypairs, and to then test their ability to reverse engineer the public keypair generation process. It is my belief that proof-for would be equally valuable as proof-against in either of these categories. Finally, we'll conclude with some number crunching on where we see this particular field heading in the future.

Alexis Hellwig

This is a derivative of the German version that you can find here. Many modifications and improvements have been made in this version. The Gaia Economy – The VisionThis new economic and monetary system is a project for structural balance. It addresses the feelings and incentives of the wealthy, the middle class, and the poor alike. Critically, this new economic and monetary system makes it significantly easier to establish genuine social-democratic systems. Instead of allowing inequality to develop unchecked – which must then be corrected by taxing the rich – the Gaia Economy preventatively stops the accumulation and hoarding of wealth from the start. A central mechanism is demurrage (a circulation-maintenance fee): money does not need to be “recaptured” through taxes; instead, a continuous stream of funds is created by the natural decay of idle balances. Technically, this means: Treasury Accrual: Idle balances pay a small fee (e.g., 0.5% per month) into a transparent Treasury. Operations & Impact: This Treasury funds system operations (security, audits) and the Impact Layer. Separation: The Impact Layer decides allocations based on transparent, verifiable criteria, but it never gates or controls the Payment Layer. Status & ImplementationThis manuscript represents the first half of the complete work; further chapters detailing advanced implementations and global scaling are forthcoming. However, we are not waiting for the text to be finished to act. The Payment Layer and Impact Layer have already been programmed. They are fully functional and ready to use as an application. This app will be released officially alongside the implementation of the first pilot project. The Gaia Economy is conceived as a learning system – errors are data that can be changed through a rigorous governance process. We invite you to build, test, and improve with us. Collaboration requests, constructive criticism, and questions are highly welcome. Contact: info@dzydent.com Abstract: The Gaia Economy (U.S. Edition) The DiagnosisThe current monetary system contains a structural flaw: positive interest and compound interest automatically shift wealth upward, generating permanent pressure for growth and rationalization. This "invisible vacuum cleaner" siphons purchasing power from the real economy into financial asset hoards. The Solution: Two Separated Modules The Gaia Economy introduces a new economic infrastructure consisting of two deliberately separated layers: Payment Layer (Gaia Coin): A neutral, non-speculative payment rail. It anchors a light circulation pressure (demurrage) in code. This ensures money keeps flowing, making hoarding unattractive. It serves as a medium of exchange, not a wealth storage vehicle. It is non-custodial and privacy-preserving (no on-chain PII), utilizing zero-knowledge proofs (ZKPs) to validate transactions without disclosing personal details. Impact Layer (Voluntary Incentives): An optional layer that rewards verifiable contributions to the common good (e.g., ecological repair, care work, education). It operates on a cash-basis: rewards (Vouchers) are paid out of realized Treasury inflows, ensuring the system never creates debt or inflation. It evaluates entities, not individuals, preventing "social credit" surveillance. Governance & SafeguardsTo prevent capture, the Gaia Economy utilizes common-good councils and a multi-quorum governance system. Changes to core parameters require a supermajority and a mandatory timelock (delay), ensuring no rule changes happen overnight. Implementation StrategyIntroduction proceeds via closed-loop pilots (municipalities, universities, merchant associations) that run in parallel with the U.S. Dollar. The Gaia Economy is positioned as complementary infrastructure – compatible across political camps – secured through clear legal frameworks (e.g., 501(c)(3) stewardship, licensed partners for fiat ramps). Executive Summary (For Decision-Makers) Starting Point & GoalThe Gaia Economy responds to structural mis-incentives in the existing monetary system (hoarding, wealth concentration, growth pressure) with a practical, legally grounded alternative that runs voluntarily in parallel to the USD. Core Solution Gaia Coin (Payment Layer): A digital cash replacement with embedded demurrage to stimulate local circulation. Architecture: Energy-efficient consensus, pseudonymous wallets, open-source code. Neutrality: Payments are never gated by behavior or AI. Impact Layer (Incentives): A voluntary layer that rewards verifiable outcomes. Mechanism: Impact Vouchers are minted for verified actions and redeemed for Gaia Coin. Pacing: Payouts are strictly paced by the Budget_k (realized treasury inflow) to ensure solvency. Verification: Relies on off-chain evidence and Human-in-the-Loop review; AI is assistive only. Governance & Compliance (U.S. Context) Immutable Core: The separation of Payment/Impact and the prohibition of positive interest are unchangeable. Parameter Registry: Adjustable parameters (e.g., demurrage rate) require Supermajority + Timelock. Compliance: Pilots start as non-custodial closed loops. Any custody or fiat interaction is handled exclusively by licensed partners (banks/MTLs), ensuring compliance with U.S. regulations without burdening the protocol. Introduction & Scaling Phase 1 (Pilot): Private, closed-loop implementation with anchor merchants and a local nonprofit. Phase 2 (Regional): Integration with municipal services and licensed on/off-ramps. Phase 3 (Network): Inter-regional connection. Benefits Short term: Faster local circulation (Velocity), reduced merchant transaction costs, transparent funding for local projects. Mid term: Measurable strengthening of care, education, and environmental protection through the Impact Layer. Long term: A socially stable, ecologically compatible economy that relies on incentives rather than coercion. Immediate Next Steps The software and the blockchain currency are ready. The path forward is execution: Sign non-controlling MOUs with pilot partners (City/University). Define the Impact Catalog v1 (verifiable metrics for local needs). Deploy the Protocol v1.0 App (Wallet + POS + Treasury Dashboard). Establish Governance (GIP process, Council selection). Deploy Monitoring (Public Dashboards for Treasury and Impact KPIs). Keywords: Gaia Economy, Demurrage, Dual-Module Economic Architecture, Cash-Basis Budgeting, Impact Vouchers, Non-Custodial, DAO Governance, Social Democracy, Justice, Fair, Anti-Hoarding, Common Good, Sustainable Development.Work to be done next:Part X – Technical Blueprint & Pilot-to-Scale Roadmap (expanded, detailed, integration-ready) Part XI – The Mathematics of GAIA (Balance Equations) (10-point micro-structure per subsection) Part XII – Environment, Animals, Public Health (Special Topics) (10-point micro-structure per subsection) Part XIII – Practice: U.S. Case Studies (10-point micro-structure per subsection)

Khasatullaev Sobirjon, Elis Mediawati, Indah Fitriani

This study examines the growth trends of cryptocurrencies and their associated taxation policies, focusing on the unique technological advancements and regulatory frameworks shaping the market. Utilizing a systematic literature review methodology, this study synthesizes findings from academic and institutional sources to explore cryptocurrency growth and global taxation policies, the research investigates the adoption metrics of major cryptocurrencies and the comparative taxation policies across various jurisdictions. Findings reveal a substantial increase in cryptocurrency adoption driven by institutional investments and technological innovations. However, taxation policies vary widely, impacting investor behavior and market dynamics. This research contributes to understanding the interplay between cryptocurrency growth and taxation, providing insights for investors and policymakers.

Yosita Saikhwan, Khwanmanee Maneechot, Kanokphol Nikornpest

This research undertakes a comparative analysis of Thailand’s anti-money laundering (“AML”) regulatory framework in relation to the most recent recommendations issued by the Financial Action Task Force (“FATF”) concerning money laundering risks associated with Security Token Offerings (“STOs”) conducted via blockchain technology. The objective is to identify potential regulatory gaps and areas for improvement in Thailand’s existing AML measures, particularly in the areas of regulatory oversight, licensing requirements, customer due diligence (“CDD”), recordkeeping obligations, and the reporting of suspicious transactions by virtual asset service providers (“VASPs”). The methodological basis of the research is the comparative analysis method, examining Thailand’s applicable AML laws and regulations alongside FATF guidelines, relevant literature, and case law. The research found that Thailand’s applicable AML laws, including the relevant regulations, are inadequacies and inefficiencies in the regulatory oversight of securities offerings that utilize emerging technologies. Specifically, the current regulatory framework is insufficient in effectively preventing or mitigating risks related to money laundering and the financing of terrorism for investors. As a result, it does not adequately ensure the security and integrity of investments in decentralized systems, therefore, it fails to provide sufficient safeguards to protect investors from inadvertently becoming involved in unlawful activities. These shortcomings indicate a lack of alignment with international standards issued by the FATF. This research is useful to legislative authorities, lawyers, law students, and regulatory bodies, especially in Thailand, and only limited to the regulation of money laundering in Thailand and does not provide empirical research.

Martin Enilov, Edna Delantar, Mamata Parhi

Fintech plays an instrumental role in advancing global ESG objectives, leveraging a more inclusive, transparent, and accountable financial system. Our paper explores the occurrence of dynamic linkages between Fintech and ESG across various dimensions, examining how the strength of their interconnectedness drives the energy transition towards clean technology. Using daily data from 31st May 2018 to 1st August 2024, we apply a time-varying parameter robust Granger causality method coupled with quantile technique to provide the first attempt in the literature on the dynamic causal patterns between the strength of Fintech-ESG connection and Cleantech energy transition risk (CETR). We find asymmetry in the connectedness across different quantiles, with Fintech sectors acting primarily as shock transmitters, while most ESG indexes are receivers. The 2022 Russia-Ukraine conflict reduces the connectedness between Fintech and ESG, with minimal effects on spillover direction. Our results show a heterogeneous response to shocks in developed markets, while developing ones tend to react more homogeneously. Additionally, we find strong evidence of a time-varying causal relationship between Fintech-ESG connectedness and CETR, with the conflict exacerbating asymmetry, especially at the lower quantile. Recent trends suggest a modest resurgence in this connection, signalling a re-emergence of the Fintech-ESG connection influence on CETR. The impact of extreme events tends to taper-off over time, suggesting that the prolonged conflict-driven market environment may have stabilized sufficiently to restore Fintech's role in promoting ESG initiatives, thereby supporting the ongoing transition to clean technology. • Fintech sectors except Distributed Ledger transmit shocks, while most ESG stocks are receivers. • Developed ESG markets heterogeneously respond to shocks, unlike developing ones. • The 2022 Russia-Ukraine military conflict reduces connectedness between Fintech and ESG. • Strength of Fintech-ESG connection impacts CETR heterogeneously across the distribution. • Time-varying causality between Fintech-ESG connectedness and CETR under different market conditions.

Z. Liu, Nianmin Yao, Shengyuan Bai, Tengyi Mai

As vehicular ad hoc networks (VANETs) increase in size and complexity, ensuring secure, flexible, and privacy-preserving vehicle-to-infrastructure (V2I) authentication remains a major challenge. Existing protocols often focus solely on identity verification, overlooking the need for access control based on vehicle attributes. Furthermore, vehicles must obtain authentication credentials from various trusted entities, including automakers, regulators, and government agencies. However, the absence of a unified credential issuance mechanism introduces fragmentation and inconsistencies during the registration process. To address these issues, we propose a V2I authentication protocol, called PriV2I, that integrates distributed credential issuance, attribute-based access control, and strong anonymity guarantees. During vehicle registration, our approach uses Shamir’s Secret Sharing with a threshold t of n across multiple certification authorities (CAs) to consolidate credentials. A vehicle credential can only be issued by a predefined threshold number of CAs, enhancing security and flexibility. Within the authentication protocol, Pointcheval-Sanders (PS) signatures enable fine-grained access control based on vehicle attributes such as type and role. Meanwhile, noninteractive zero-knowledge proofs protect identity privacy by allowing vehicles to prove credential possession and policy compliance without revealing sensitive information. The proposed scheme also supports batch authentication at Roadside Units (RSUs) to efficiently handle high-density environments and includes a comprehensive revocation mechanism to trace and revoke malicious vehicles promptly and securely. In our implementation, the computation cost during the authentication phase is 75.58 ms. The communication overhead per authentication exchange is 992 bytes across two messages. Overall, the protocol provides a secure, scalable, and privacy-preserving solution tailored to modern VANET environments.

Piotr Fiszeder, Witold Orzeszko, Radosław Pietrzyk, Grzegorz Dudek

This study advances the understanding of Bitcoin volatility forecasting by analysing an extensive set of 62 explanatory variables, including cryptocurrency market behaviour, Google search trends, financial indices, and economic indicators. We employ Bayesian Model Averaging (BMA), Least Absolute Shrinkage and Selection Operator (LASSO), and Random Forest (RF) methods to assess variable importance and forecast accuracy. Our research demonstrates that LASSO and RF models incorporating exogenous variables significantly improve both daily and weekly Bitcoin variance forecasts compared to models using only lagged Bitcoin volatilities. Key factors influencing Bitcoin volatility include lagged realised variances, trading volume, and Google search intensity. The study reveals that the impact of these variables on Bitcoin volatility is time-varying, reflecting its evolving relationship with broader economic indicators and market sentiment. Our findings contribute to the literature by providing a comprehensive analysis of Bitcoin volatility drivers, evaluating the effectiveness of variable transformations, and comparing the performance of advanced forecasting methods in handling the cryptocurrency's extreme volatility. These insights are valuable for researchers, investors, portfolio managers, and policymakers navigating the dynamic cryptocurrency market.

Mallikarjun Reddy Gouni

Financial crime detection faces unparalleled challenges as criminal networks exploit digital payment channels, cryptocurrency platforms, and cross-border transaction systems outside traditional monitoring frameworks. In this respect, AFCI introduces a novel framework for federated machine learning, regulatory reasoning engines, and real-time risk propagation analytics to build unified global privacy-preserving anti-crime intelligence ecosystems. The framework lets organizations train collaborative models with decentralized institutions, safely aggregating information from multiple parties without sharing sensitive transaction data by means of secure aggregation protocols and differential privacy mechanisms. Large language models coupled with knowledge graphs automate the processes of regulatory interpretation and rule generation, and graph neural networks enable the detection of coordinated criminal activities on a large scale in transaction networks through temporal message passing mechanisms. Reinforcement learning agents continuously optimize detection policies to balance the identification of genuine threats against the goal of minimizing false alarms. The framework bridged critical gaps in cross-border compliance coordination and empowered institutions to develop shared detection capabilities in support of data localization requirements and an array of diverse regulatory frameworks. Long-term security of privacy-preserving federated computation would be guaranteed with post-quantum cryptography. This convergence of advanced technologies allows next-generation financial crime prevention systems to remain effective against evolving criminal methodologies while preserving fundamental privacy rights.

K. Venkata Reddy

Demand volatility, logistical interruptions, and linked worldwide networks define the remarkable complexity of modern supply chains. Classic centralized management solutions find difficulty in offering real-time solutions to changing operational problems. For designing distributed, intelligent, and self-organizing supply chain ecosystems, artificial intelligence agents combined with Model-Control-View (MCV) architectures provide transformational possibilities. These autonomous computational entities span three functional layers: view interfaces enable monitoring and interaction, control mechanisms govern decision-making and optimization, and model components represent digital twins of supply chain entities. Multi-agent coordination enables decentralized yet coherent operations through the negotiation and collaboration of agents representing suppliers, production, logistics, and retail, all of which adhere to standardized protocols. Applications include demand forecasting, intelligent logistics, stock optimization, supplier partnering, and flexible disruption response. While reducing reliance on centralized control systems, the framework enhances resilience, scalability, openness, and operational efficiency. Challenges in implementation include organizational adaptation needs, cybersecurity vulnerabilities, and data integration complexity. Future advances in autonomous and cooperative supply chain systems will include explainable artificial intelligence, quantum-enhanced optimization, edge computing powers, and blockchain-enabled trust mechanisms.

Sharma, Hirsh

How may digital platforms be redesigned to better serve the interests of the artists whose creative work gives them value? An artist- and user-owned streaming platform is proposed that would decentralize control and redistribute revenue from corporations to creators. Using Web3 infrastructure, the model enables direct artist payment through blockchain-based transactions that scale based on user consumption, minimizing fees and ensuring transparency. The design also emphasizes community governance and localized music discovery to encourage the regrowth of music culture. By reducing reliance on profit-driven intermediaries, the system aims to create a sustainable environment where independent artists can thrive. Spotify exemplifies how a platform’s designed-in incentives can perpetuate exploitation. The social construction of technology framework suggests that Spotify’s ownership model, pro- rata payment system, and algorithmic design prioritize shareholder value over fairness. Spotify’s supposed mission to “unlock the potential of human creativity” is undermined by its own architecture, which locks artists into dependency. Together, these projects show that achieving fairness in a digital music economy requires not only reforming compensation models but rethinking the infrastructures that define creative labor itself.

Mutiullah Shaikh, Uffe Kock Wiil, Ali Ebrahimi, Yumna Memon

Blockchain technology has revolutionized digital systems by ensuring trust, transparency, decentralization, and security. However, in the democratic nature of blockchain networks, there is a huge underlying dependency on consensus mechanisms, but the challenges associated with these, such as energy costs, network attacks, preservation of privacy, centralization, and limited scalability, hinder miners and stakeholders from adopting appropriate consensus mechanisms. In this paper, we present a conceptual literature overview of most consensus mechanisms by highlighting potential areas of exploration and considerations before adopting blockchain technology for various applications. This exploration turned our focus toward analyzing three prominent underlying aspects of consensus mechanisms, i.e. energy consumption, security, and decentralization. A simulation-based comparative analysis of five prominent blockchain consensus mechanisms, such as Proof of Work (PoW), Proof of Stake (PoS), Delegated Proof of Stake (DPoS), Proof of Authority (PoA), and Proof of Capacity (PoC), is presented in various network load scenarios to further evaluate their performance metrics. The simulated metrics were cross-validated using empirical data from real blockchain networks (e.g., Ethereum, Bitcoin, VeChain, and Chia) collected between 2022 and 2025, ensuring alignment between theoretical performance models and observed on-chain behavior across diverse consensus mechanisms. Results overall indicate that PoW excels in decentralization and security while costing the highest energy, making it less scalable for high-throughput scenarios. PoS balances energy efficiency and moderate decentralization, while DPoS achieves scalability at the expense of decentralization. PoA and PoC are shown to be energy-efficient alternatives, but vary in their levels of centralization and security. Our findings constitute a comprehensive guide for researchers, miners, and practitioners aiming to optimize blockchain performance for diverse applications.

Ayush Nainwal, Atharva Kamble, Nitin Awathare

Public blockchains inherently offer low throughput and high latency, motivating off-chain scalability solutions such as Payment Channel Networks (PCNs). However, existing PCNs suffer from liquidity fragmentation-funds locked in one channel cannot be reused elsewhere-and channel depletion, both of which limit routing efficiency and reduce transaction success rates. Multi-party channel (MPC) constructions mitigate these issues, but they typically rely on leaders or coordinators, creating single points of failure and providing only limited flexibility for inter-channel payments. We introduce Hypergraph-based Multi-Party Payment Channels (COALESCE), a new off-chain construction that replaces bilateral channels with collectively funded hyperedges. These hyperedges enable fully concurrent, leaderless intra- and inter-hyperedge payments through verifiable, proposer-ordered DAG updates, offering significantly greater flexibility and concurrency than prior designs. Hence our, design eliminates routing dependencies, avoids directional liquidity lock-up, and does not require central monitoring services such as watchtowers. Our implementation on a 150-node intra-hyperedge achieves a transaction success rate of approximately 94% under heavy load (larger payment sizes), while full hyperedge evaluation over a 15,000-node network sustains success rates in the range of 85% to 95%, without HTLC expiry or routing failures, highlighting the robustness of COALESCE.

Junyi Fan, Li Sun

Decentralized lending protocols, exemplified by Aave V3, have transformed financial intermediation by enabling permissionless, multi-chain borrowing and lending without intermediaries. Despite managing over $10 billion in total value locked, empirical research remains severely constrained by the lack of standardized, cross-chain event-level datasets. This paper introduces the first comprehensive, event-driven data infrastructure for Aave V3 spanning six major EVM-compatible chains (Ethereum, Arbitrum, Optimism, Polygon, Avalanche, and Base) from respective deployment blocks through October 2025. We collect and fully decode eight core event types -- Supply, Borrow, Withdraw, Repay, LiquidationCall, FlashLoan, ReserveDataUpdated, and MintedToTreasury -- producing over 50 million structured records enriched with block metadata and USD valuations. Using an open-source Python pipeline with dynamic batch sizing and automatic sharding (each file less than or equal to 1 million rows), we ensure strict chronological ordering and full reproducibility. The resulting publicly available dataset enables granular analysis of capital flows, interest rate dynamics, liquidation cascades, and cross-chain user behavior, providing a foundational resource for future studies on decentralized lending markets and systemic risk.

Alan J. McNamara, Sara Shirowzhan, Samad M.E. Sepasgozar

Purpose This study identifies and validates opportunities for automation of problematic construction contract administrative tasks and processes. Through the evaluation of identified automation opportunities, system features are proposed and prioritised to form a development roadmap for future intelligent contract (iContract) creation and evolution. Design/methodology/approach This study applies a qualitative approach to draw on experienced construction practitioners with direct knowledge of contract administration practices. Thematic mapping and co-occurrence analysis of interview data identify “Contract Process Automation Opportunities” (CPAOs) which are then evaluated and prioritised to inform a development roadmap. Findings The study establishes ten evaluation criteria, specific to contract processes and identifies eight novel CPAOs. Ten iContract system features, along with the technological and environment requirements to facilitate development, are then synthesised into the novel iContract development roadmap. Research limitations/implications An “iContract system requirements identification model” is developed by adapting established process automation theoretical frameworks. This guided the structured selection of suitable automatable contractual processes, based on both theoretical and practical insights. The roadmap offers a practical guide for iContract developers for an initial artefact and future researchers aiming to overcome the evolutionary challenges highlighted. Practical implications The roadmap offers a practical guide for iContract developers for an initial artefact and future researchers aiming to overcome the evolutionary challenges highlighted. Originality/value This study contributes a unique and founding iContract system development roadmap, in an embryonic field, that has been borne and validated by industry practitioners. It identifies the initial functions to successfully develop an iContract artefact and highlights the evolution of the concept towards an autonomous solution.