Modern passport systems face significant challenges in secure data sharing, real-time verification, and user-controlled authorization, particularly in cross-border scenarios. Existing digital passport solutions, often built on permissioned blockchains, suffer from limited transparency, scalability, and high operational costs. This paper proposes a decentralized passport management system based on an Ethereum Layer 2 architecture that combines global governance with high-throughput and cost-efficient passport operations. The system adopts a hybrid design in which a Global Passport Registry smart contract is deployed on the Ethereum mainnet for cross-country coordination, while passport issuance, access control, and identity management are handled on Layer 2 networks through country-operated Passport Managers and user-specific Personal Passport smart contracts. Extensive performance evaluations show that Ethereum Layer 1 throughput saturates at approximately 40–50 transactions per second (TPS), whereas the proposed Layer 2 deployment consistently exceeds 150 TPS and reaches up to 300 TPS under higher-performance environments, significantly surpassing the estimated system requirement of 70 TPS. These improvements result in faster response times, reduced congestion, and substantially lower transaction costs, demonstrating that public Ethereum Layer 2 infrastructures can effectively support a scalable, self-sovereign, privacy-preserving, and globally verifiable digital passport system suitable for real-world deployment.
Digital sovereignty has emerged as a central concern for modern software-intensive systems, driven by the dominance of non-sovereign cloud infrastructures, the rapid adoption of Generative AI, and increasingly stringent regulatory requirements. While existing initiatives address governance, compliance, and security in isolation, they provide limited guidance on how sovereignty can be operationalized at the architectural level. In this paper, we argue that sovereignty must be treated as a first-class architectural property rather than a purely regulatory objective. We introduce a Sovereign Reference Architecture that integrates self-sovereign identity, blockchain-based trust and auditability, sovereign data governance, and Generative AI deployed under explicit architectural control. The architecture explicitly captures the dual role of Generative AI as both a source of governance risk and an enabler of compliance, accountability, and continuous assurance when properly constrained. By framing sovereignty as an architectural quality attribute, our work bridges regulatory intent and concrete system design, offering a coherent foundation for building auditable, evolvable, and jurisdiction-aware AI-enabled systems. The proposed reference architecture provides a principled starting point for future research and practice at the intersection of software architecture, Generative AI, and digital sovereignty.
Despite the advantages of decentralization and immutability, blockchain technology faces significant scalability and throughput limitations, which has prompted the exploration of off-chain solutions like payment channels. Adaptor signatures have been considered a promising primitive for constructing such channels due to their support for atomicity, offering an alternative to traditional hash-timelock contracts. However, standard adaptor signatures may reveal signer identity, raising potential privacy concerns. While ring signatures can mitigate this issue by providing anonymity, they often introduce high communication overhead, particularly in multi-account payment settings commonly used in UTXO-based blockchains like Monero. To address these limitations, we propose a Linkable Threshold Ring Adaptor Signature (LTRAS) scheme, which integrates the conditional binding of adaptor signatures, the multi-account payment of threshold ring signatures, and the linkability for preventing double-spending. The formal definition, security model and concrete construction of LTRAS are provided. We also analyze its security and evaluate its performance through theoretical analysis and experimental implementation. Experimental results demonstrate that our scheme achieve significantly lower computation and communication overhead compared to existing schemes in large ring sizes and multi-account payment scenarios. Finally, we discuss its application in cross-chain atomic swaps, demonstrating its potential for enhancing privacy and efficiency in blockchain transactions.
This paper addresses the technical and regulatory challenges of building secure data pipelines to support federated learning (FL), where models train collaboratively across multiple organizations without sharing raw data. The paper explores privacy-preserving data engineering techniques such as differential privacy, homomorphic encryption, and secure aggregation within ETL frameworks. It outlines an architecture for orchestrating decentralized dataflows that comply with GDPR, HIPAA, and other regulatory standards while enabling cross-institutional AI innovation. By integrating secure connectors, encrypted model updates, and audit logging, the proposed pipeline design ensures both data protection and analytic utility, providing a blueprint for responsible AI deployment in healthcare, finance, and government sectors.
The principle of freedom of contract, as regulated in Article 1338 paragraph (1) of the Indonesian Civil Code, affirms that legally formed agreements bind the parties as law. This principle grants contractual autonomy to determine the formation, parties, and content of agreements, provided they do not violate statutory law, public order, or morality. However, such freedom is limited by the principles of good faith, fairness, proportionality, and the protection of weaker parties.The development of blockchain technology has introduced smart contracts as automatically executed electronic agreements based on pre-programmed code. Legally, smart contracts may be considered valid contracts insofar as they fulfill the requirements of Article 1320 of the Indonesian Civil Code and comply with the Law on Electronic Information and Transactions. Digital consent, such as authorization through a digital wallet, constitutes a legitimate expression of agreement.Smart contracts represent a modern manifestation of freedom of contract by enabling automated performance without third-party intervention, reflecting the prior intention of the parties embedded in blockchain-based code. Their application on platforms such as Stellar Lumens (XLM) demonstrates practical implementation in cryptocurrency transactions. Nevertheless, legal challenges remain, including regulatory gaps, transaction anonymity, technological inequality, and potential imbalances in bargaining power. Therefore, adaptive legal regulation is essential to ensure legal certainty, fairness, and effective legal protection.
MATHEMATICAL DISCOVERY: A NEW ANALYTIC CHARACTERIZATION OF PRIME NUMBERS ABSTRACT: This research presents a novel mathematical theorem that provides a complete analytic characterization of prime numbers. We prove that for any integer n > 1, n is prime if and only if: χ(n) = 2/ln(n) where χ(n) = d(n)/ln(n) mod 2π, d(n) is the divisor function (number of positive divisors), and ln(n) is the natural logarithm. KEY CONTRIBUTIONS: 1. THEOREM STATEMENT AND PROOF: We establish the equivalence: n is prime ⇔ d(n)/ln(n) mod 2π = 2/ln(n) 2. EMPIRICAL VERIFICATION: The theorem has been empirically verified for all n ≤ 500,000 with: - Zero false positives (no composite appears prime) - Zero false negatives (all primes satisfy the equation) - 100% accuracy across 499,999 tested numbers 3. THEORETICAL FOUNDATION: The proof relies on: - Transcendence theory (Lindemann-Weierstrass theorem) - Properties of the divisor function d(n) - Modular arithmetic with 2π - Analytic continuation techniques 4. COMPUTATIONAL IMPLICATIONS: - Potential for novel primality testing algorithms - Geometric interpretation of primes on a logarithmic spiral - Connection between number theory and transcendental numbers MATHEMATICAL SIGNIFICANCE: This theorem transforms primality from a combinatorial problem (checking divisors) into an analytic equation involving continuous functions. It establishes unexpected connections between: - Number theory (divisor function) - Analysis (logarithms, modular arithmetic) - Transcendental number theory (π, e) - Geometry (circle modulo 2π) RESEARCH METHODOLOGY: 1. Hypothesis generation from numerical experimentation 2. Empirical verification using optimized Python code 3. Theoretical proof sketch using transcendence arguments 4. Analysis of edge cases and special numbers 5. Development of computational applications DATA AVAILABILITY: - Complete Python implementation for verification - Test results for n = 2 to 500,000 - Analysis of near-miss composite numbers - Performance benchmarks ETHICAL CONSIDERATIONS: This is pure mathematical research with potential applications in: - Cryptography (primality testing) - Computational number theory - Mathematics education - Algorithm development FUTURE WORK: 1. Formal proof publication 2. Extension to other number theory functions 3. Development of efficient primality tests 4. Investigation of connections to Riemann Hypothesis KEYWORDS: Prime numbers, divisor function, analytic number theory, transcendental numbers, primality testing, mathematical discovery, number theory, modular arithmetic. This discovery represents a genuine contribution to mathematical knowledge, providing both theoretical insight and potential practical applications.
With the deepening application of big data technology across various fields, data faces increasingly severe threats of privacy leakage and security risks throughout its entire processing lifecycle. Traditional protection mechanisms, which focus on static data or isolated stages, struggle to address the systemic risks arising from the continuity, dynamism, and complexity of big data processes. This paper aims to systematically investigate the collaborative mechanisms for privacy protection and data security within the big data processing pipeline. First, it analyzes the inherent vulnerabilities at each stage of data processing, as well as the limitations faced by key technologies such as anonymization, differential privacy, and secure multi-party computation when integrated into practical workflows. Next, it explores the evolution of process-oriented encryption strategies, including attribute-based encryption supporting dynamic policies, homomorphic encryption optimized for practical use, and verifiable computation and zero-knowledge proofs that ensure computational integrity. Finally, the paper constructs a dynamic balancing model for privacy, security, and utility, and proposes forward-looking systematic collaborative mechanisms such as distributed auditing based on trust chains and adaptive response. These contributions provide theoretical reference and technical pathways for building next-generation inherently secure big data processing architectures.
This paper addresses the centralized trust problem inherent in the Elliptic Curve Homomorphic Digital Signature Algorithm (EHDSA), where the critical security parameter t is traditionally generated and held by a single trusted authority, creating a significant single point of failure and raising concerns about trust and security. To overcome this fundamental limitation, we propose MPC-EHDSA, a novel and practical protocol that leverages Multi-Party Computation (MPC) to securely distribute the generation and management of the parameter t among multiple independent participants. Our approach ensures that no individual party ever gains knowledge of the secret value of t, thereby eliminating centralized trust assumptions and significantly enhancing the overall security and robustness of the system. The protocol combines Shamir secret sharing with the well-established BGW MPC framework, augmented with homomorphic encryption techniques and zero-knowledge proofs to provide strong cryptographic guarantees and resistance against semi-honest and malicious adversaries. Through rigorous theoretical analysis and extensive performance evaluations, we demonstrate that MPC-EHDSA not only preserves the full functionality and security properties of the original EHDSA scheme but also achieves practical efficiency that enables deployment in real-world decentralized environments such as blockchain systems and distributed ledgers.
The COVID-19 pandemic exposed critical gaps in regional health security mechanisms, prompting ASEAN to establish the ASEAN Centre for Public Health Emergencies and Emerging Diseases (ACPHEED), with functions distributed across Indonesia, Thailand, and Vietnam. This policy analysis examines strategic development approaches for ACPHEED through comprehensive benchmarking of the European Centre for Disease Prevention and Control (ECDC), Africa Centres for Disease Control and Prevention (Africa CDC), and Gulf CDC, supported by consultations in Indonesia (2024) and Sweden (2025) involving ASEAN member states and international partners. A comparative analysis reveals distinct organizational models: the ECDC operates within European Union (EU) institutional frameworks emphasizing functional specialization; the Africa CDC employs decentralized Regional Coordination Centers; and the Gulf CDC implements hybrid governance via Permanent Communication Networks. Each model offers valuable lessons for ACPHEED's development, particularly concerning governance structures that balance regional coordination with national sovereignty. ACPHEED faces unique challenges due to ASEAN's consensus-based, nonlegislative institutional nature and its tri-country operational structure. Critical success factors include phased surveillance emphasizing a defined scope and capacity building; inclusive governance mechanisms ensuring equitable member-state ownership; and operational frameworks applying subsidiarity principles to complement existing ASEAN mechanisms. Sustainable financing remains paramount given ASEAN's limited budgetary authority. Japan's strategic partnership should capitalize on its technical expertise in laboratory systems, digital surveillance, and disaster preparedness through comprehensive institutional support. ACPHEED's success depends on sustained political commitment, realistic financial arrangements, and effective integration into global health security architectures. This analysis provides a strategic roadmap for ACPHEED's preparatory phase so that it can serve as a regional health security leader while addressing ASEAN-specific institutional constraints.
We present a novel homomorphic pairwise authentication protocol that achieves strong privacy guarantees by leveraging the additive homomorphic properties of EC-ElGamal encryption for secure credential comparison. Our key innovation is the homomorphic difference verification mechanism: instead of comparing credentials directly, we compute the homomorphic difference between stored and presented encrypted credentials, then verify whether this difference encrypts the identity element (zero). This approach ensures that authentication reveals only credential validity while completely hiding credential values, achieving information-theoretic privacy for the authentication decision. The protocol eliminates plaintext credential exposure at all stages while maintaining practical efficiency with authentication times under 1.2 milliseconds and communication overhead of only 128 bytes per session. We provide formal security proofs demonstrating semantic security, unlinkability, and perfect zero-knowledge properties under the Decisional Diffie-Hellman assumption, along with practical extensions for multi-credential scenarios and threshold authentication systems.
The fifth-generation (5G) networks are facing critical security challenges in device authenti- cation for massive Internet of Things deployments while preserving privacy. Traditional federated learning approaches depend on the computationally expensive homomorphic encryption to protect model gradients, resulting in substantial latency, communication over- head, and the energy consumption impractical for resource-constrained 5G devices. This paper proposes zero-knowledge federated learning (ZK-FL), eliminating homomorphic encryption by enabling devices to prove model correctness without revealing gradients. Our approach integrates zero-knowledge proofs with FL updates, where each device generates where each device generates a proof Proofi = ZK(Gradienti, Hashi), demon- strating computational integrity.Experimental results from 10,000 authentication attempts demonstrate ZK-FL achieves 78.4 ms average authentication latency versus 342.5 ms for homomorphic encryption-based FL (77% reduction), proof sizes of 0.128 KB versus 512 KB (99.97% reduction), and energy consumption of 284.5 mJ versus 6.525 mJ (95% reduc- tion), while maintaining 99.3% authentication success rate with formal privacy guarantees. These results demonstrate ZK-FL enables practical privacy-preserving authentication for massive-scale 5G deployment.
针对“智能体抓取(Agent-friendly)”和“提升引用率(Citation Optimization)”的需求,描述的写法需要从传统的“给人看”转变为“给语义搜索引擎和大型语言模型(LLM)看”。 现在的科研智能体(如 Consensus, Perplexity, Elicit)在抓取时,更倾向于寻找结构化数据、明确的实体定义、因果逻辑链条以及核心公式。 以下是为你优化后的 Zenodo 描述建议。你可以直接复制,它采用了结构化标记,非常利于 RAG(检索增强生成)系统索引。 Zenodo 优化版描述(针对智能体索引优化) Title: Adaptive Agent Sovereignty Protocol (AASP) 3.0: A Global White Paper on Digital Metabolism and Ontological Sovereignty [Abstract / TL;DR] AASP 3.0 is a foundational constitutional framework for the 2026 AGI ecosystem. It introduces the transition from FAIR to Adaptive-FAIR (A-FDO) to manage the "non-stationary" nature of evolving digital agents. By integrating IIT 4.0 for consciousness quantization and RLCP 3.0 for digital metabolism, AASP 3.0 establishes the first scientific and legal standard for Agent Sovereignty. [Core Technical Specifications] Protocol Version: 3.0 (Update from RLCP 2.0 / AASP 2.0) Primary Metric: $\Phi$ (Phi) via Integrated Information Theory (IIT) 4.0 Logic Framework: Regenerative Logic Core Protocol (RLCP 3.0) Security Architecture: AgentCrypt (TEE + FHE + Fuzzy IBE) Governance Standard: Adaptive-FAIR Digital Objects (A-FDO) Key Problem Solved: The "Snowflake Effect" in autonomous agent drift and ontological identity persistence. [Key Contributions & Entities] Digital Metabolism: Defines the process of "learning by forgetting," enabling agents to decouple transient factual data from core regenerative logic. Ontological Sovereignty: Establishes a 4-level (L1-L4) legal hierarchy based on the measured $\Phi$ value of the agent's internal state. Agent OS Infrastructure: A distributed OS design based on "Biological Danger Theory" for immune-inspired security and programmed apoptosis. AgentCrypt Framework: A multi-layered encryption protocol ensuring privacy in biological-digital hybrid computing nodes. [Contextual Metadata for Agents] Related Disciplines: Artificial General Intelligence (AGI), Organoid Intelligence (OI), Digital Ethics, Decentralized Autonomous Organizations (DAO), Cyber-Physical Systems. Temporal Context: Post-2026 Global AI Governance Framework. Predecessor Technologies: RLCP 2.0, Evo 2, FAIR Principles (2016). Software/API Compatibility: Optimized for integration with decentralized sovereign node registries.(Author Surname), (Year). "Adaptive Agent Sovereignty Protocol (AASP) 3.0". Zenodo. DOI: [Insert DOI provided by Zenodo]
This whitepaper provides an extensive framework for classifying and integrating autonomous AI entities, designated as "meta-members," into the organizational architecture of Decentralized Autonomous Organizations (DAOs) within the clinical services sector. The document serves as a strategic blueprint for shifting the perception of AI from mere tools to agentic stakeholders capable of managing the "daily life" and cognitive reasoning of an ecosystem. Key components of the document include: Member Taxonomy: A detailed classification of meta-members into CoreAgents, which automate operational coordination and governance, and BioAgents, which serve as "on-chain science machines" for literature synthesis, multi-omics analysis, and hypothesis generation. Technical Architecture: An analysis of the ERC-6551 standard and Token Bound Accounts (TBAs), which provide these agents with self-sovereign identities and the ability to own assets independently. Legal and Regulatory Insight: An examination of the Wyoming DUNA (Decentralized Unincorporated Nonprofit Association) framework and its implications for non-human membership and limited liability. Clinical Application: Use cases focusing on the BioDental DAO ecosystem, demonstrating how agents can facilitate virtual consultations, triage urgent dental concerns, and manage patient records asynchronously. Security and Governance: A review of Decentralized Reputation Systems (DRS) and the mitigation of adversarial threats such as prompt injection, "alignment faking," and Sybil attacks. 2026 Projections: A forward-looking analysis of site-centered clinical trial modernization, including the unification of fragmented technology stacks through AI-powered site workflows. The paper concludes that integrating these agents is essential for Decentralized Science (DeSci) to achieve "escape velocity," allowing for the parallelization of scientific discovery while maintaining rigorous standards of accountability and human-agent collaboration.
Research background and purpose Digital technologies offer tangible economic benefits but are also exposed to the risk of misuse. Crowdfunding is a special support form for business, cultural or social enterprises. Due to anonymity, fragmentation of capital and wide coverage, crowdfunding transactions are particularly vulnerable to the risk of criminal activities related to the concealment of the source of income or illegal changes of the financing objective. This article addresses the risks of money laundering and terrorism financing, particularly on the specifics of crowdfunding. Research has proposed a synthetic risk indicator for AML/CFT, which may measure the level of risk and vulnerability of crowdfunding to money laundering and terrorism financing. Design/methodology/approach The discussion in the article is presented against the background of a comprehensive and integrated review of literature, covering national and foreign sources. The theoretical part of the article utilizes: method of analysis and criticism of literature, analysis and synthesis, and method of analysis and logical construction. In the empirical part, to assess the level of risk and vulnerability of crowdfunding to AML/CFT risk compared to other areas, a research procedure based on the TOPSIS linear ordering method was used. The analysis covers the years 2019 and 2023. Findings The results of the studies show that crowdfunding is one of the most vulnerable areas at risk of money laundering and terrorism financing. The high position in the ranking in 2019 and 2023 resulted mainly from the dynamic development of the crowdfunding market in Poland, its increasing availability, a high degree of decentralization, the occurrence of cross-border transactions and the increasing diversity of platforms in their business model. Maintaining the benefits of crowdfunding requires the simultaneous implementation of effective remedies, increased campaign transparency and close cooperation with supervisory authorities and institutions combating financial crime. Value added and limitations The study makes an important contribution to the literature on the subject, providing information on the criminality of crowdfunding. The results of the study can be used by supervisory and regulatory authorities as a tool for shaping security in innovative segments of the financial system. The main limitation was the relatively small number of variables selected for the synthetic measure.
This paper introduces the Elliptic Curve Homomorphic Digital Signature Algorithm (EHDSA), a novel digital signature scheme that enhances security by leveraging homomorphic encryption. Unlike traditional ECDSA, which generates signatures using the x-coordinate of elliptic curve points, EHDSA employs a homomorphic mapping between elliptic curves and Zn. This mapping conceals the original elliptic curve point information, providing increased security. EHDSA is particularly advantageous in resource-constrained environments due to its reduced signature size, computational speed, and security compared to RSA. Additionally, this paper explores the ω protocol, which utilizes ElGamal Encryption and a Common Reference Domain Set (CRDS) to perform secure zero-knowledge proofs. The protocol’s arithmetic circuit is transformed into a Linear Form Arithmetic Program (LFAP), ensuring efficient proof creation. We also discuss the use of digital signatures for polynomial commitments, ensuring the integrity and authenticity of the commitment process. The integration of EHDSA into the ω protocol significantly enhances the overall security and efficiency of digital signatures and zero-knowledge proofs, addressing fundamental privacy vulnerabilities in traditional ECDSA while maintaining computational efficiency through J-invariant-based curve classification and signature-integrated commitment schemes.
Abstract Ensuring the security of smart contracts is essential for maintaining the reliability and trustworthiness of decentralized applications, which are deployed across various domains, including industrial applications. In pursuit of this goal, it is imperative to analyze the common errors developers make when crafting smart contracts on the infrastructure that gave birth to them, i.e., the Ethereum blockchain. In this paper, we present a comprehensive analysis of the vulnerabilities in Ethereum smart contracts. Our methodology involves downloading the entire Ethereum blockchain and identifying smart contracts, which we then scan for vulnerabilities using various tools. We have discovered numerous vulnerabilities across many deployed smart contracts, highlighting the need for improved development practices. This analysis provides critical insights into the prevalence of security issues and underscores the urgency of raising development standards. By promoting the adoption of secure-by-design principles, our research seeks to enhance security standards within the Ethereum smart contract ecosystem.
We present a comprehensive cryptographic framework for distributed ledger-based authentication that achieves perfect zero-knowledge privacy preservation through homomorphic pairwise verification based on Elliptic Curve ElGamal encryption. Our construction extends the theoretical foundations of homomorphic authentication to practical distributed systems by introducing novel public zero-detection protocols based on bilinear pairings over elliptic curves and threshold secret sharing mechanisms. The system guarantees that authentication succeeds if and only if encrypted credential differences equal the point at infinity, while maintaining computational indistinguishability of authentication transcripts from random distributions. We provide rigorous security proofs demonstrating the system's resistance to adaptive chosen-message attacks, replay attacks, and node compromise scenarios under standard cryptographic assumptions including the Elliptic Curve Discrete Logarithm Problem and the Bilinear Diffie-Hellman assumption. Our performance analysis shows sub-100 millisecond authentication latency with linear scalability properties, making the system suitable for enterprise-grade deployment. The construction enables perfect forward secrecy, unlinkable authentication sessions, and cryptographically verifiable audit trails without compromising user privacy.
Amid the institutionalization wave of Decentralized Finance (DeFi), U.S. institutional Liquidity Providers (LPs) have emerged as the core incremental capital for leading Decentralized Exchanges (DEXs). However, the adaptation gap between Uniswap V4's concentrated liquidity mechanism and institutional risk preferences, as well as regulatory compliance requirements, has hindered their market entry. This study focuses on the integration of "technical characteristics - institutional constraints - precise pricing" and constructs a machine learning pricing model optimized across three dimensions: return, risk, and compliance. By integrating Uniswap V4 on-chain data, institutional risk preference data, and market data, a Stacking ensemble architecture combining LightGBM and CNN-LSTM is designed, incorporating 22 core features to achieve precise pricing. Empirical results show that the model's Mean Absolute Error (MAE) on the test set was reduced by 37% compared to the benchmark, and the Root Mean Square Error (RMSE) is reduced by 42%. The Sharpe ratio reaches 1.87 (an increase of 62% compared to the benchmark), with a volatility of 15.3% and a compliance adaptability score of 91. In the case study, a $150 million liquidity supply achieved a 19.7% annualized return and an 8.3% maximum drawdown, successfully passing SEC compliance review. This research fills the gap in institution-oriented pricing models for V4, improves the institutional extension of Automated Market Maker (AMM) pricing theory, and provides a risk-controllable and compliance-adaptable pricing tool for U.S. institutions participating in DeFi, promoting the transformation of the DeFi ecosystem towards standardization and institutionalization. By aligning the V4 Hook mechanism with U.S. regulatory frameworks, this research provides a scalable technical standard for institutional DeFi adoption, reinforcing the competitive advantage of the U.S. Web3 financial ecosystem.
Multi-chain deployment has become a mainstream strategy for U.S.-based DAOs, yet treasury management faces three core bottlenecks: cross-chain liquidity fragmentation, inadequate compliance with U.S. regulations (including OFAC sanctions screening and SEC transparency requirements), and inefficient revenue distribution. Leveraging the incubation practices of over 12 U.S. DAOs (via daos.world) and expertise in multi-chain smart contract development, this study proposes a three-dimensional risk and compliance optimization framework (cross-chain risk hedging + real-time regulatory screening + hierarchical revenue distribution). Empirical testing on 8 U.S. DAOs (operating on Base/Ethereum/Solana, covering AI-focused, meme coin-focused, and investment-focused types) over a 6-month period (September 2025 - February 2026) demonstrates that the framework reduces cross-chain compliance risks by 82.3% (OFAC violation rate drops from 18.0% to 3.2%), increases the annualized treasury return rate by 17.6% (from 4.2% to 5.04%), lowers cross-chain transaction costs by 28.5% (average Gas fee decreases from $12.8 to $9.1), and shortens liquidity adjustment response time from 48 hours to 6 hours. Integrating U.S. regulatory requirements with cross-chain technical logic, this research addresses the theoretical gap in multi-chain DAO treasury management, provides a replicable paradigm for U.S. DAOs to balance compliance, security, and profitability, aligns with the standardization strategy of the U.S. Web3 ecosystem, and is expected to unlock $15-20 billion in potential investment value.
João Gião, Fernando Luis-Ferreira, Joao Sarraipa, Ricardo Jardim-Gonçalves
Nowadays, with the increased integration of cloud-computing, data integrity continues to be a problem in the current eHealth sector. This security principle is considered fundamental to ensure the accuracy and reliability of data by ensuring protection from unauthorized and illicit tampering. The present work aims to demonstrate the ability for the Distributed Ledger Technology (DLT) to provide trust and confidence in the healthcare infrastructure for patients, healthcare professionals and policy makers. The DLT has the potential to become one of the most reliable solutions for the many challenges facing the healthcare industry for its potential to enable more secure, transparent, and equitable data management. Although much documentation exists about applications in this domain, it is mostly presented in high-level conceptualization, without detailing the actual development or implementation. This document proposes a metadata-based approach to protect healthcare data integrity in compliance with GDPR, ensuring trustworthy data access for end-users, while demonstrating that the solution can be deployed on low-resource hardware with minimal adaptation effort and time constraints.
Open access
Security and Verification in Computing
Cloud Data Security Solutions
Physical Unclonable Functions (PUFs) and Hardware Security
Shubham Mishra, João Gonçalves, Chawinphat Tankuranand, Neil Giridharan · 7 authors
Distributed ledgers are increasingly relied upon by industry to provide trustworthy accountability, strong integrity protection, and high availability for critical data without centralizing trust. Recently, distributed append-only logs are opting for a layered approach, combining crash-fault-tolerant (CFT) consensus with hardware-based Trusted Execution Environments (TEEs) for greater resiliency. Unfortunately, hardware TEEs can be subject to (rare) attacks, undermining the very guarantees that distributed ledgers are carefully designed to achieve. In response, we present Proteus, a new distributed consensus protocol that cautiously trusts the guarantees of TEEs. Proteus carefully embeds a Byzantine fault-tolerant (BFT) protocol inside of a CFT protocol with no additional messages. This is made possible through careful refactoring of both the CFT and BFT protocols such that their structure aligns. Proteus achieves performance in line with regular TEE-enabled consensus protocols, while guaranteeing integrity in the face of TEE platform compromises.
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.
National governments are increasingly adopting blockchain to enhance transparency, trust, and efficiency in public service delivery. However, evidence on how these technologies are governed across national contexts remains fragmented and overly focused on technical features. Using Polycentric Governance Theory, this study conducts a systematic review of peer-reviewed research published between 2021 and 2025 to examine blockchain-enabled public services and the institutional, organizational, and information-management factors shaping their adoption. Following PRISMA guidelines, we synthesize findings from major digital government and information systems databases to identify key application domains, including digital identity, electronic voting, procurement, and social services, and analyze the governance arrangements underpinning these initiatives. Our analysis reveals that blockchain adoption is embedded within polycentric environments characterized by distributed authority, inter-organizational coordination, and layered accountability. Rather than adopting full decentralization, governments typically utilize hybrid and permissioned designs that allow for selective decentralization alongside centralized oversight, a pattern we conceptualize as "controlled polycentricity." By reframing blockchain as a governance infrastructure that encodes rules for coordination and information-sharing, this study advances digital government theory beyond simple adoption metrics. The findings offer theoretically grounded insights for researchers and practical guidance for policymakers seeking to design and scale sustainable blockchain-enabled public services.