This dissertation investigates the crime of money laundering in the context of cryptoasset acquisition, from a functional-reductive perspective of criminal law. The central objective is to establish precise and coherent criteria for the incidence of criminal norms, aiming to limit the irrationality of punitive power and promote a counter-selective application, without compromising the accountability for complex criminal typologies. The study is pursued through a bibliographic review, analyzing national and international doctrine, legislation, and jurisprudence, complemented by interdisciplinary sources from economics, technology, and sociology. The first chapter establishes the theoretical premises of Zaffaroni's negative/agnostic theory of punishment and the reductive penal system. Criminal law, from this perspective, functions to limit punitive power. The second chapter delves into the crime of money laundering, analyzing its evolution, phases, the affected legal interest (socioeconomic order, with a focus on free competition and initiative), and its typical elements, based on the established theoretical framework. The third chapter comprehends the phenomenon of cryptoassets, detailing the functioning of Bitcoin and blockchain, the universe of decentralized finance (DeFi), forms of acquisition, and the Brazilian regulatory framework. The fourth chapter applies the dogmatic framework to the analysis of money laundering's typicality in different forms of cryptoasset acquisition and discusses the aggravating factor for the use of virtual assets. The research achieves its general objective by demonstrating a path for criminal dogmatics to establish precise criteria and limits for the incidence of money laundering, legitimizing judicial decisions by curbing punitive arbitrariness. Criteria are established to identify typical and atypical cases of money laundering involving cryptoasset acquisition, and requirements are set for the application of the special aggravating factor, conditioning it on the concrete demonstration that the use of cryptoassets intensified the harm to the legal interest. The interdisciplinary approach and consideration of the Brazilian reality are crucial to reject the trivialization of the institute and fulfill the counter-selective function of the penal system, preventing the automatic imputation of this serious crime without a proper technological understanding and knowledge of money laundering's limits
The deployment of distributed digital twin systems in sectors such as healthcare, manufacturing, and critical infrastructure has significantly heightened the importance of data privacy. These systems interact with numerous devices and users, increasing the risk of data leakage or unauthorized access to sensitive information. Traditional centralized identity management and access control mechanisms no longer meet the scalability, autonomy, and privacy requirements of modern distributed architectures. This article explores how smart contracts operating in blockchain environments can provide decentralized access management for digital twin systems. Smart contracts enable transparent and reliable enforcement of access policies without relying on centralized authorities. The study examines the integration of modern cryptographic technologies into smart contract workflows, including zero-knowledge proofs, decentralized identifiers (DIDs), and confidential computing. These technologies make it possible to verify access rights and perform secure operations without revealing sensitive data. The article also analyzes the limitations of existing solutions, such as the high transaction costs of public blockchains, the limited performance of traditional smart contracts, and the challenges of integrating confidential computing into resource-constrained devices. The authors outline future research directions, including optimizing Layer 2 architectures to improve performance, developing secure auditing mechanisms, and ensuring compatibility with self-sovereign identity systems. The conclusions emphasize that privacy should be treated as a fundamental property of digital twin systems. In these environments, smart contracts must serve not only as governance logic but also as trusted agents that guarantee compliance with access policies and regulatory requirements in decentralized ecosystems.
Sustainable trade requires verifiable, granular, and trustworthy data across multi-jurisdictional supply chains. This paper argues that blockchainâs binding constraints are institutional, not technical, and proposes the Green Trade Blockchain Governance Trilemma: no design can simultaneously maximize (i) transactional efficiency, (ii) regulatory verifiability, and (iii) decentralized governance with commercial privacy. Comparative casesâTradeLens, IBM Food Trust, Everledger, and Power Ledgerâshow divergent institutional choices and outcomes: TradeLens faltered under perceived hegemonic control; Food Trust succeeded via a buyer mandate; Everledger thrived through symbiosis with trusted authorities; Power Ledger scaled within a regulatory sandbox. We further analyze the Oracle Problem as the key limit to verifiability and assess privacy-enhancing technologies, especially zero-knowledge proofs, as partial mitigations that protect sensitive data while enabling compliance checks. We conclude that success hinges on context-specific institutional designâcertified oracles plus verifiable computationârather than a one-size-fits-all stack, offering actionable guidance for policymakers, consortia, and firms building credible green-trade infrastructure.
Blockchain technology was first developed to support Bitcoin, but it has come a long way since then and is now used for more than just money. It features a clear and decentralized structure that changed a lot of industries, especially those that deal with money and managing the supply chain. In the supply chain industry, blockchain makes it easier to trace things, cuts down on fraud, and speeds up operations. Blockchain makes it possible for decentralized finance (DeFi) platforms to work with financial institutions. This makes it easier for more people to use financial services and lowers the cost of transactions. This paper investigates the substantial impacts of blockchain technology across several industries, emphasizing adoption challenges like as scalability and regulatory hurdles, while exploring its benefits, challenges, and practical applications.
Smart contracts underpin contemporary decentralized systems, yet their immutability and perpetual execution amplify the consequences of latent defects. Despite progress in manual audits, static analysis, fuzzing, and formal verification, auditors face a widening gap between the scalability and desired assurance due to limited automation capability. Recent large language models (LLMs) with tool-use capabilities promise greater automation, but monolithic single-agent auditors struggle with coverage, robustness, and reproducibility. Motivated by addressing these issues, we propose Multi-Agent Auditing (MAA), a framework that coordinates a team of tool-grounded agents through a constrained protocol that privileges verifiable artifacts. Besides, we mechanize an LLM-assisted orchestration mechanism and a shared knowledge base to coordinate a set of agents specialized in sophisticated testing approaches to produce budget-aware and evidence-centric audit results. Furthermore, we present the experiment results showing that MAA outperforms singleLLM auditors and provide empirical insights into LLM-backend selection.
The symbiotic radio network (SRN) plays a crucial role in green communication solutions by facilitating cooperative communication between devices of primary and secondary links, leading to enhanced transmission quality and optimized resource efficiency. For the joint demodulation of primary and secondary signals, the multiparty trust is essential for operators with different interests. Building multiparty trust in a decentralized manner is challenging for the implementation of the SRN. As an emerging distributed ledger technology, blockchain provides multiparty trust between unreliable devices to share data and resources cooperatively. This paper proposes a consortium Blockchain-based Cooperative Communication scheme for SRN (BCC-SRN), where Hyperledger Fabric is used as the trust anchor with better security, higher throughput, and more flexible organization. In particular, a credit-based incentive mechanism is established to encourage different parties to behave according to the negotiated contracts. The credit is recorded by smart contracts and adjusted based on the contribution of the corresponding cooperators. Simulation results prove that the proposed BCC-SRN is highly effective in improving cooperation security and transmission quality.
Lokman Kantar, Tarana Azimova, Murat Akkaya, Yildirim Hasan-Huseyin
This study investigates the volatility dynamics and time-varying correlations between Bitcoin (BTC) and major financial and commodity markets, including gold, oil, NASDAQ, NIKKEI, FTSE, DAX, and the U.S. Dollar Index (USDINX). Using daily data and GARCH-family models, we quantify persistence, asymmetry, and mediumterm memory in BTC volatility. Model selection using loglikelihood, SIC, and AIC criteria identifies EGARCH asthe best model for capturing conditional variance behavior. We then employ a DCC-MGARCH framework to estimate evolving cross-market correlations. Results indicate that BTC volatility is highly persistent, exhibits stronger reactions to negative shocks, and shows moderate mean reversion. Gold displays the lowest persistence, confirming its role as a stable diversifier. DCC-MGARCH estimates reveal weak positive BTC-Gold correlations, negative BTC-USDINX correlations, and no significant BTC-Oil or BTC-DAX linkages, implying substantial diversification potential. Notably, BTC-NIKKEI correlations strengthened during the COVID-19 period, while BTC-Gold correlations modestly increased. These findings underscore the importance of dynamic portfolio strategies, as optimal weights shift in response to evolving conditional covariances, rendering static allocations suboptimal. For policymakers, volatility persistence and correlation thresholds can inform leverage and exposure limits, particularly when the linkages between BTC and traditional assets intensify.
This study aims to analyze the regulations applicableto Bitcoin in force in seven Latin American countries to assess the need to strengthen the regulatory framework and its implementation in the region. For this purpose, a qualitative study was designed with an exploratory scope and a non-experimental cross-sectional approach. Information is collected from secondary sources throughthe web and a survey of academics from institutions affiliated with the ALAFEC. The results show the regulatory advances regarding cryptocurrencies. Current regulations are described for Argentina, Brazil, Chile, Colombia, El Salvador, Mexico, and Venezuela. All the countries analyzed have mechanisms for the prevention of money laundering, terrorist financing, and the use of resources of illicit origin. Nonetheless, it is necessary to strengthen the current regulations by including mechanisms for the protection of all participants. The results show the normative advances regarding the regulation of cryptocurrencies. Current regulations are described for Argentina, Brazil, Chile, Colombia, El Salvador, Mexico, and Venezuela. All the countries analyzed have mechanisms for the prevention of money laundering, the financing of terrorism, and the use of resources of illicit origin. Nonetheless, it is necessary to strengthen the current regulations by including mechanisms for the protection of all participants.
Cryptocurrencies have emerged miraculously all over the globe due to their legitimacy, transparency, immutability, and the traceability that blockchain technology provides. However, the benefits it provides are dwarfed by how unpredictable and extremely price-volatile the cryptocurrencies are. That makes it really tough for investors to find their profitable opportunities in such volatile markets. Social media sources, like Twitter and Reddit, have evolved as crucial tools of sentiment estimation above the explosively volatile price movements of decentralized currencies. Here we introduce an attention-based hybrid CNN-LSTM model optimized for social media sentiment analysis to use them towards investment decisions in a broad portfolio of cryptocurrencies. The existing Convolutional Neural Network (CNN) effectively extracts the essential features, and Long Short-Term Memory (LSTM) has the potential to capture the long dependencies between phrases. Although these models can process massive textual data, they limit treating all the features equally important. Therefore, the proposed model induces the attention mechanism into hybrid CNN-LSTM for emphasizing more or fewer weights on different words according to their contributions and optimizes the parameters of employed neural networks using grid search. In our pipeline, the attention-augmented CNN-LSTM first transforms each tweet/review into a 512-dimensional task-specific embedding; a calibrated radial-basis SVM then serves as the final decision layer, refining the margin for classes that the neural network alone tends to blur. This sequential ('deep-features-plus-SVM') architecture boosts F1 by 3.2 pp over a pure Softmax head while adding only 0.4 ms of inference time. Extensive experiments conducted on cryptocurrency-related tweets and Reddit reviews reveal the outperformance of the proposed model over existing Deep Neural Networks (DNNs) and state-of-the-art models. Trained on 9.9 k crypto-tweets and 33 k Reddit comments, AEH attains 98.7% accuracy, 0.987 F1, and Îș = 0.94, outperforming strong baselines (pure LSTM + 8.3 pp; pure CNN + 19.3 pp) and the widely-used VADER toolkit (+ 11.8 pp). On the forecasting side, a complementary GRU regressor trained on eight-year price series yielded MAE = 0.0315, MAPE = 5.95%, and MSE = 0.0022 for Bitcoin, beating an ARIMA benchmark at p < 0.001. The primary objective of the proposed hybrid model attributed to processing huge social sentiments with an attention mechanism to break the dilemma of cryptocurrency investors.
The article addresses the issue of ensuringconfidential exchange of personal data in inter-organizationalinformation systems under conditions of increasing digitalinteraction between public and private sector entities. It is notedthat centralized models for processing and exchanging personaldata fail to provide an adequate level of protection againstunauthorized access, transaction tampering, and do not ensuresufficient transparency of data operations. These limitationshinder full compliance with regulatory requirements, particularlythe provisions of the General Data Protection Regulation(GDPR), ISO/IEC 27001 and 27701 standards, as well asnational legislation on information protection. The study substantiates the feasibility of using a permissioned blockchain as the architectural basis forimplementing a secure, decentralized exchange of personal datawith guaranteed access control, transaction audit, and dataimmutability. A conceptual model of the information system isproposed, involving smart contracts for managing data subjectconsent, access control, and the integration of the InterPlanetaryFile System (IPFS) for robust off-chain data storage. The modelalso includes the use of Zero-Knowledge Proof (ZKP) cryptographic mechanisms and behavioral verification criteriafor transactions. Particular attention is given to risk analysis associated withpersonal data processing in inter-organizational environments, and to the application of supplementary protection toolsâsuchas masking, pseudonymization, and data perturbationâtomitigate potential losses in the event of data leakage. A set oftechnical and organizational compliance criteria withinternational and national information security standards isoutlined. The aim of this research is to design an architectural modelfor inter-organizational personal data exchange based onpermissioned blockchain that ensures confidentiality, integrity, controlled access, and regulatory compliance in the field ofinformation protection.
Securities trading systems have settlement efficiency, audit transparency, and fraud prevention concerns due to centralized intermediaries and aging infrastructure. Existing research models risk counterparty trading due to delayed settlements, opaque record keeping, and human compliance checks. The study aims to design and evaluate a blockchain-based equities trading platform for transaction security and traceability. Provable Atomic Consensus for Trading (PACT), a blockchain-based architecture for regulated financial institutions' trading environments, combines hybrid consensus with a privacy-preserving cryptographic approach. A hybridized consensus process for efficient transaction finality, zero-knowledge proof enabled atomic settlements for instant delivery vs. payment while protecting commercial secrecy, and regulator-accessible smart contracts for real-time compliance checks are used in the PACT algorithm PACT found a 20% reduction in consensus finality time, 53% reduction in proof verification time, 56% improvement in smart contract vulnerability, and 42% improvement in auditability index on a permissioned blockchain with hardware-accelerated smart contracts. The study indicated 35.6% lower throughput and 41.7% lower Tx volume over 10 validators. Latency over 10 validators is 24% lower and Tx volume is 23.2% lower than existing research models. Blockchain improves securities infrastructure speed, reliability, and transparency without affecting compliance, according to studies.
The US Department of Transportation (USDOT) delivers a wide range of infrastructure projects, backed by a fiscal year 2023 budget exceeding $100 billion. These projects face mounting pressures to meet performance, accountability, and delivery standards, driven by their dependence on public funding and their operational complexity. Transportation infrastructure presents sector-specific challengesâsuch as time-sensitive user disruptions, multiparty coordination, and asset intersection risksâthat demand more robust, automated, and transparent project delivery mechanisms. Blockchain-enabled smart contracts have emerged as a promising solution to address these operational pain points through real-time automation, immutable data records, and decentralized transaction processing. However, the practical realities of the transportation sectorâits fragmented systems, regulatory layers, and diverse stakeholder interfacesâcreate unique integration challenges that remain underexamined. To address this, this study investigates how smart contracts can be effectively integrated into transportation infrastructure by identifying the context-specific needs, requirements, capabilities, and challenges that govern their adoption. A three-phase research design was employed. First, a literature review was conducted to extract generalized integration factors for smart contract use in the broader construction domain. Secondly, these factors were evaluated and ranked by qualified transportation experts to reflect their relevance in sector-specific contexts. Thirdly, structural equation modeling (SEM) was used to analyze expert survey responses and isolate the most influential integration drivers. The results indicate that, unlike general construction projects, the top integration priorities in transportation include (1) compliance checking for quality management (needs); (2) integration with existing cloud repositories or enterprise platforms (requirements); (3) the ability to maintain immutable records (capabilities); and (4) uncertainty regarding usability (challenges). These findings provide a targeted knowledge base for practitioners and policymakers, outlining the critical considerations required for effective and sector-sensitive implementation of smart contracts in transportation infrastructure.
Toby Brooks, Joel Farrell, Matthew Hernandez, Adam J. McKee · 6 authors
ABSTRACT Through the American Council on Education, the Carnegie Foundation introduced the Elective Classification of Leadership for Public Purpose (ECâLPP) in 2022. Application for this formal recognition is a voluntary but rigorous process involving the gathering and presentation of a variety of evidence of institutional indicators, concluding with a thorough thirdâparty review and status decision. The designation was initially piloted in partnership with 13 institutions, with 9 founding institutions successfully completing the process in 2021; however, no published work to date was available to provide guidance or insight for the next application round (American Council on Education, 2023). The purpose of this article was to describe the process employed at a Carnegie Special Focus Institution whereby an interdisciplinary team of stakeholders was charged to create, convene, and deploy the necessary processes and information in order to make an application for the 2024 cycle. Given the relative newness of the designation and the interest in the ECâLPP designation by a variety of institutions across the country, it was anticipated that the process employed and lessons learned locally would be beneficial for other individuals and/or institutions considering future application(s). Summary Collaborative Framework for ECâLPP Application: The paper outlines a 6âweek strategic process involving interdepartmental collaboration, emphasizing the importance of leadership, teamwork, and stakeholder engagement for institutions pursuing the Carnegie Elective Classification for Leadership for Public Purpose (ECâLPP). Challenges in Organizational Structure: The manuscript highlights the complexities posed by decentralized structures, such as autonomous academic units, which can hinder cohesive data collection and narrative alignment, underscoring the need for institutionâwide coordination. Strategic Insights for Leadership Programs: The authors identify gaps in learner engagement in leadership initiatives and suggest expanding leadership frameworks to include studentâfacing programs, ensuring institutional alignment with ECâLPP's public purpose objectives. Lessons from the Feedback Process: Though the initial application was unsuccessful, the review panel's feedback provided actionable insights for improving future submissions, such as articulating leadership initiativesâ impact more broadly and refining assessment methods to demonstrate institutional commitment to leadership development.
This study provides a structured literature review of consumer behaviour in the metaverse, exploring motivations for metaverse use, adoption, avatar engagement, virtual goods purchases, non-fungible tokens (NFTs), and the impact of brand experiences on real-world product purchase intentions. For this purpose, a systematic review of peer-reviewed articles published over the past two decades was conducted. From an initial pool of 209 articles retrieved from electronic databases, 36 met the inclusion criteria and were thematically analysed. Key trends, knowledge gaps, and future research directions were identified. A novel adaptation of the engagement framework was proposed, categorizing consumer behaviour in the metaverse into three stages: pre-engagement, engagement, and post-engagement. The review reveals that Second Life is the most studied platform, with surveys being the predominant research method. Research has primarily focused on retail, fashion, and tourism, particularly virtual product purchases. Despite providing valuable insights, existing studies reveal substantial research gaps and limited theoretical development. The proposed framework organizes recurring themes and provides a foundation for future research, highlighting the need for empirical evidence to further advance the field. This study is one of the first to systematically review consumer behaviour research in the metaverse and propose a stage-based framework, contributing to theoretical understanding and offering structured directions for future empirical research. JEL Classification: M31; O32; Q55 Article History: Received: June 30, 2025; Reviewed: September 5, 2025; Accepted: September 22, 2025; Available online: September 29, 2025.
Industry 5.0 is a hot topic in the current technological business scenario. Industry 4.0 has not reached its full potential as of now, and Industry 5.0 can help Industry 4.0 to target a 100% adoption rate by using it as a base and inculcating human centricity, better traceability, enhanced transparency, better coordination, and sustainability. Industry 5.0 is a far more, holistic approach and it has a wider scope in associating with upcoming technologies such as-6G (for faster, safer, and more stable real-time communication); Decentralized Autonomous Organization enhances the capabilities of decision-making, and also supports decentralized decision-making at the time of crisis; and Parallel Intelligence increases safety as well as capability to have self-healing systems and enhanced human centricity. This paper tries to explain various components of Industry 5.0. Additionally, it aims to fill the gap in the literature and effectively provide future research directions, with an emphasis on the interplay between the components of Industry 5.0, rating systems for Industry 5.0, and the broader Industry 5.0 ecosystem and governance. This paper uses data from ScienceDirect, IEEE Xplore, and Google Scholar databases. We conclude this study by suggesting the need for more empirical research in this domain.
Hancheng Gao, Mohammad S. Obaidat, Haiping Huang, Yizheng Xing · 6 authors
The adoption of blockchain technology in healthcare has significantly enhanced data integrity, transparency, and user privacy. However, high storage overhead and resource-intensive operations remain major challenges to its widespread deployment, particularly in large-scale or resource-constrained healthcare environments. To address these challenges, we propose STORChain, a storage-optimized blockchain framework designed for data services in healthcare. The framework introduces the Clustered Merkle Patricia Tree (C-MPT), a novel logical structure that aggregates similar transaction types to maximize storage efficiency while ensuring Proof of Inclusion (PoI). A Selective Transaction Pruning Strategy (STPS) is employed to prioritize and prune essential historical data, improving data access efficiency. Additionally, an incentive-based Delegated Proof-of-Stake (DPoS) consensus algorithm is utilized, integrating a probabilistic election mechanism to promote fairness and node inclusivity. Comprehensive theoretical analysis and practical experiment results indicate that STORChain significantly reduces storage overhead, optimizes data access, and outperforms existing schemes.
Zero-Knowledge Proofs (ZKPs) enable users to prove knowledge of certain information without disclosing the information itself. Multi-ID ZKP systems extend this concept, allowing individuals to submit anonymous yet verifiable com plaints across various platforms while maintaining privacy and accountability. This paper explores the integration of ZKPs into complaint management systems, addressing the challenges of anonymity, verifiability, scalability, and computational efficiency. By reviewing existing literature on ZKP applications in authentication, identity management, and scalable systems, we identify key advancements and research gaps. This work aims to establish a foundation for implementing robust, privacy preserving, and efficient complaint systems leveraging multi-ID ZXP mechanisms.
ABSTRACT Nonâfungible tokens (NFTs) are digital assets that represent the ownership of unique items that can be bought or sold using cryptocurrency. This comprehensive analysis of NFT involved a literature search conducted in February 2025. A total of 963 publications were initially identified from the Scopus database. Following meticulous screening, analysis, and evaluation, 734 relevant and highâquality documents were selected for further examination, employing rigorous discussions, voting, and critical appraisal. The literature review on NFTs highlighted several frequently coâoccurring keywords, including Blockchain, Smart Contracts, Commerce, Ethereum, Digital Assets, Metaverse, Decentralization, Digital Storage, Cryptocurrency, and Distributed Ledger. This study organizes NFT research into 10 distinct categories through a combination of review and text mining techniques. These categories include âpricing, marketing, and investment,â âapplication of NFTs,â âart,â âgames and metaverse,â âbenefits, drawbacks, and review papers,â âsecurityâ, âlaw and ownership,â âsystem for NFT and extending of NFT,â âSupply chain management,â and âAI.â For each category, the research questions and their corresponding answers are mapped. Additionally, the study developed a comprehensive framework to establish connections between research categories, providing valuable insights into expanding NFT adoption. Finally, this research investigates the challenges associated with the application of NFTs and explores potential future research directions.
The rise of Web3 and Decentralized Finance (DeFi) has enabled borderless access to financial services empowered by smart contracts and blockchain technology. However, the ecosystem's trustless, permissionless, and borderless nature presents substantial regulatory challenges. The absence of centralized oversight and the technical complexity create fertile ground for financial crimes. Among these, money laundering is particularly concerning, as in the event of successful scams, code exploits, and market manipulations, it facilitates covert movement of illicit gains. Beyond this, there is a growing concern that cryptocurrencies can be leveraged to launder proceeds from drug trafficking, or to transfer funds linked to terrorism financing. This survey aims to outline a taxonomy of high-level strategies and underlying mechanisms exploited to facilitate money laundering in Web3. We examine how criminals leverage the pseudonymous nature of Web3, alongside weak regulatory frameworks, to obscure illicit financial activities. Our study seeks to bridge existing knowledge gaps on laundering schemes, identify open challenges in the detection and prevention of such activities, and propose future research directions to foster a more transparent Web3 financial ecosystem -- offering valuable insights for researchers, policymakers, and industry practitioners.
Essossinam Pali, Coffi Cyprien Aholou, François Paul Yatta
After several hesitant attempts, Togo has made renewed progress in implementing sustainable decentralization. Municipal and regional elections held in 2019 and 2024 marked a significant institutional step forward. However, this implementation phase remains marked by both achievements and structural challenges. This article explores how local elected officials perceive the decentralization policy and its financing in their municipalities. It formulates the general hypothesis that decentralization fosters the implementation of local public policies when supported by appropriate institutional mechanisms. Based on a quantitative survey conducted in early 2024 among 487 local actors including 477 municipal councilors and 10 prefects the results highlight a range of perceptions. While some elected officials acknowledge improvements in service delivery and institutional support (through tools such as FACT and ANFCT), others stress the persistence of constraints related to financial autonomy, administrative capacities, and citizen participation. The findings suggest that decentralization in Togo is progressing, albeit unevenly, and requires further efforts to consolidate its institutional and operational foundations.
Moritz Grundei, Vipindev Adat Vasudevan, Kishori Konwar, Muriel Medard
The data availability problem is a central challenge in blockchain systems and lies at the core of the accessibility and scalability issues faced by platforms such as Ethereum. Modern solutions employ several approaches, with data availability sampling (DAS) being the most self-sufficient and minimalistic in its security assumptions. Existing DAS methods typically form cryptographic commitments on codewords of fixed-rate erasure codes, which restrict light nodes to sampling from a predetermined set of coded symbols. In this paper, we introduce a new approach to DAS that modularizes the coding and commitment process by committing to the uncoded data while performing sampling through on-the-fly coding. The resulting samples are significantly more expressive, enabling light nodes to obtain, in concrete implementations, up to multiple orders of magnitude stronger assurances of data availability than from sampling pre-committed symbols from a fixed-rate redundancy code as done in established DAS schemes using Reed Solomon or low density parity check codes. We present a concrete protocol that realizes this paradigm using random linear network coding (RLNC).
Decentralization has an important geographic dimension that conventional metrics, such as stake distribution, often overlook. Where validators operate affects resilience to regional shocks (e.g., outages, natural disasters, or government intervention) as well as fairness in reward access. Yet major blockchain protocols do not encode geographical location in their rules; instead, validator locations emerge from a combination of economic incentives, regulatory constraints, infrastructure availability, and validator deployment choices. When certain locations offer systematic advantages, validators may strategically co-locate to maximize expected rewards, as observed in Ethereum, where validators cluster along the Atlantic corridor, which exhibits favorable latency. In this paper, we propose a formal model of validators' geographical positioning incentives under Ethereum's protocol design, capturing the interaction between its two block-building paradigms, local and external block building, and the geographical distribution of validators and information sources. We analytically characterize the model under a mean-field approximation and complement this analysis with an agent-based simulation calibrated with real-world latency data to quantify how these incentives translate into geographical concentration under heterogeneous geographic and infrastructural conditions. Our results show that Ethereum's block-building architecture is not geographically neutral. Both paradigms generate location-dependent payoffs and incentives to relocate closer to payoff-relevant parties in order to reduce propagation delays, although through different underlying mechanisms. Asymmetric access to information sources further amplifies geographical centralization. We also demonstrate that consensus parameters, such as attestation thresholds and slot times, modulate latency sensitivity and can amplify these effects, acting as protocol-level levers. Finally, we discuss the implications of our findings for protocol design and outline potential mitigation directions informed by our analysis.