Abstract: The research presents a Privacy-Preserving Data Exchange (PPDE) framework for electronic health records (EHRs) that integrates elliptic-curve cryptography (ECC), zero-knowledge proofs (ZKPs), and capability tokens on a permissioned blockchain to create a cohesive, policy-compliant data-sharing workflow. In this system, IoT gateways establish ECC-based session keys to encrypt measurements at the edge, while only cryptographic hashes and pointers to the encrypted data are stored on a consortium blockchain, ensuring data confidentiality with tamper-evident integrity and auditable provenance. Healthcare providers issue Access Request Transactions that include ECC signatures and ZKPs to prove policy compliance (such as patient consent and role-based access) without revealing sensitive details. Off-chain ZKPs validate authorization decisions, with on-chain records providing verifiable evidence of conformance and access history, and a capability token is granted to authorize future data access within defined scopes and time windows. The framework emphasizes end-to-end confidentiality, privacy-preserving authorization, and tamper resistance through the blockchain. Our evaluation analyzes network throughput, end-to-end delay, packet delivery ratio, scalability, and energy efficiency, with particular attention to the overhead from blockchain operations, ECC, and ZKP verification. Results show improved privacy and security for EHR data, with only nominal overhead relative to the privacy and integrity gains, and favorable scalability and energy performance in realistic deployments.
The modern development of decentralized ledger and blockchain technologies has led to the emergence of smart contracts, which are becoming an important tool in the digital economy, transforming existing understandings of the conclusion and fulfillment of obligations in the digital environment. The authors believe that recognizing the objective multi-paradigmatic nature of this phenomenon will not only facilitate the integration of modern technological advances into the legal system but also stimulate the growth of an innovative economy, increase trust in digital platforms, and ensure their adaptation to the rapidly changing conditions of the digital market. The conclusions include proposals for legislative development based on a multi-paradigmatic approach, which assumes a comprehensive understanding of the legal status of smart contracts, taking into account technological, legal, and socioeconomic aspects. This, according to the authors, will help identify the most promising ways to integrate digital contractual instruments into the modern legal system.
Smart contract security mainly aims to discover vulnerabilities in contract code based on the assumption that malicious behavior emerges from exploitable execution paths. This assumption is increasingly misaligned with modern blockchain systems, where off-chain automated agents continuously observe on-chain state and act autonomously. In this paper, we argue that smart contracts now act as public signalling mechanisms, capable of encoding command-and-control (C2) primitives through events and persistent storage variables. Off-chain agents, including LLM-based agents, convert benign-looking state changes into coordinated, high-impact actions across protocols and chains, semantically interpreting these signals. This kind of behaviour does not require code-level exploitation and thus can be built to evade existing analysis methods by construction. We explore how such a kind of coordination enables delayed activation, selective targeting, and deception, and explain why contract-centric security models fall short of such risks. We conclude by examining the main challenges and the directions for securing agent-mediated blockchain ecosystems.
Energy Communities (ECs) have emerged as central legal instruments for decentralized renewable energy deployment across Europe; however, their long-term viability depends critically on financial sustainability mechanisms that remain inadequately understood. This study examines the economic foundations of ECs through a narrative literature review of revenue generation, cost allocation, and the capital mobilization pathways in three representative European markets (Germany, Spain, and Italy). A structured Scopus database search identified 280 peer-reviewed studies published between 2019 and 2025. Following systematic screening, 89 articles were selected for analysis through bibliometric mapping in R (Biblioshiny) and qualitative synthesis in NVivo. The analysis reveals that stable feed-in tariffs, tax incentives, and self-consumption remuneration schemes form the primary revenue mechanisms, while cost management effectiveness varies substantially across countries due to differing grid-charge structures and administrative frameworks. Capital access remains constrained for smaller communities despite hybrid financing innovations combining public grants, cooperative equity, and emerging crowdfunding mechanisms. Regulatory heterogeneity, high upfront investment requirements, and limited institutional credit availability continue to impede scalability. The findings emphasize that achieving widespread EC adoption requires harmonized policy frameworks, transparent cost-sharing arrangements, and diversified investment instruments that align local participation with national decarbonization objectives while ensuring equitable access across diverse socio-economic contexts.
Why does the pursuit of "correct answers" and optimization suffocate modern organizations in the AI era? This paper analyzes Uniqlo (Fast Retailing) not merely as an excellent company, but as a "Generative Circular Enterprise" that structurally refuses to crystallize. It serves as a survival manifesto using Universal Phase Crystallization Theory (UPCT) to shift corporate OS from static management to dynamic Generativity. Highlights The Shift in Era: Contrasts the failure of traditional "S-origin" (Plan-driven) management in the population onus era with Uniqlo's "Φ-origin" (Generation-driven) adaptability. Structural Fluidity: Reveals how the absence of a "Corporate Planning Department" functions as a deliberate mechanism to prevent the fixation of strategy (S) and maintain organizational metabolism. Epistemology of Execution: Reinterprets "1% Plan, 99% Execution" not as spirit, but as a rational cycle of discarding static maps (S) to navigate the fluid reality (Φ). Purpose as OS: Defines "Global One" and "LifeWear" not as static slogans, but as a distributed operating system that enables autonomous decentralized processing. The AI Trap: Warns that using AI for mere optimization shrinks the "basin of attraction," and proposes using AI as a "solvent" to melt rigid structures. Summary Modern corporations face a paradox: the more they utilize data and AI to optimize efficiency, the more they lose vitality and resilience. This paper diagnoses this pathology as the "Curse of Crystallization" defined by Universal Phase Crystallization Theory (UPCT). Traditional organizations fixate on "Correct Answers (S)" derived from past data, creating rigid structures that cannot adapt to the "Generative Flow (Φ)" of the population onus era. Uniqlo (Fast Retailing) presents a counter-model. By reversing the management vector to Φ→G→S, Uniqlo starts with formless will and market intuition, crystallizing them into provisional products only to immediately deconstruct and regenerate them. This "Non-Fixed Structure"—exemplified by the lack of a central planning department and the fluid leadership of Tadashi Yanai—allows the giant enterprise to move with the agility of a startup, constantly surfing the phase transition between order and chaos. Finally, the paper addresses the critical challenge of the Artificial Intelligence era. If AI is used solely to reinforce past success models (S, it accelerates organizational rigidity (the shrinking of the basin of attraction). We argue that the role of human intelligence is to act as a "Generator" that utilizes AI to melt frozen concepts, ensuring the organization remains a living, metabolic system. This is a proposal for shifting from a "Snapshot Ontology" to a "Life-OS" in business management. Author’s Related Works Ohumi, K. (2025). Manifesto of the Life OS: The "It from Wave" Philosophy. Zenodo. https://doi.org/10.5281/zenodo.18106437 Ohumi, K. (2025). A Sampling-Theoretic Reinterpretation of Quantum Uncertainty and Wave Function Collapse. Zenodo. https://doi.org/10.5281/zenodo.18004579 Ohumi, K. (2025). Observation as Operational Crystallization: Resolving Quantum Paradoxes. Zenodo. https://doi.org/10.5281/zenodo.18220191 Ohumi, K. (2025). It from Wave: Phase Propagation as Physical Basis of Information. Zenodo. https://doi.org/10.5281/zenodo.18256968 Ohumi, K. (2025). Ontological Reconstruction of Quasi-Particles. Zenodo. https://doi.org/10.5281/zenodo.18140041 Ohumi, K. (2025). Envelopment over Unification: Recovering Einstein’s Dream. Zenodo. https://doi.org/10.5281/zenodo.18244683 Ohumi, K. (2025). Sampling, Horizons, and Recurrence: Reframing Thermal Pure States and Black Hole Information. Zenodo. https://doi.org/10.5281/zenodo.18364507 Ohumi, K. (2025). π Paradox: Relation-First Information and the Geometry of Meaning. Zenodo. https://doi.org/10.5281/zenodo.18204829 Ohumi, K. (2025). Dark Energy as a Diffusive Phase of a Relational Universe. Zenodo. https://doi.org/10.5281/zenodo.18081786 Ohumi, K. (2025). Envelopment Ethics: Generativity-First Inclusion. Zenodo. https://doi.org/10.5281/zenodo.18256968 Ohumi, K. (2025). Enveloping the Free Will–Determinism Divide. Zenodo. https://doi.org/10.5281/zenodo.18287169 Ohumi, K. (2025). Rationality without Transition. Zenodo. https://doi.org/10.5281/zenodo.18193256 Ohumi, K. (2025). Over-Immune Infosphere: When Protection Becomes Rigidity. Zenodo. https://doi.org/10.5281/zenodo.18149385 Ohumi, K. (2025). The KPI Trap: Over-Optimization and Meaning Collapse. Zenodo. https://doi.org/10.5281/zenodo.18264106 Ohumi, K. (2025). The WGS Model: The Implementation of Generative Governance. Zenodo. https://doi.org/10.5281/zenodo.18308450 Ohumi, K. (2025). Envelopment Integration: Reuniting Ethics, Well-Being, and Value. Zenodo. https://doi.org/10.5281/zenodo.18332397 Ohumi, K. (2025). Resonant Management. Zenodo. https://doi.org/10.5281/zenodo.18162380 Ohumi, K. (2025). Resonant Politics. Zenodo. https://doi.org/10.5281/zenodo.18180888 Ohumi, K. (2025). Demographic Decline and Environmental Crisis as Ontological Outcomes. Zenodo. https://doi.org/10.5281/zenodo.18197092 Ohumi, K. (2025). Population Onus as an Ontological Crisis. Zenodo. https://doi.org/10.5281/zenodo.18356710 Ohumi, K. (2026). Universal Phase Crystallization Theory (UPCT) Phase I: A Unified Resolution of Quantum Paradoxes via Temporal Sampling. Zenodo. https://doi.org/10.5281/zenodo.18230537 Ohumi, K. (2026). A Phase Theory of Intelligence and Mind: Reframing Cognition as Generative–Crystallization Dynamics under Universal Phase Crystallization Theory (UPCT). Zenodo. https://doi.org/10.5281/zenodo.18430732 Ohumi, K. (2026). Universal Phase Crystallization Theory (UPCT) Phase II: A Phase Transition Law for Generative Systems under Measurement Optimization. Zenodo. https://doi.org/10.5281/zenodo.18408708 Ohumi, K. (2026). Why "Correct" Ideologies Freeze Societies: A UPCT-Based Structural Analysis of Ideological Crystallization from Antiquity to the 20th Century. Zenodo. https://doi.org/10.5281/zenodo.18437668 Ohumi, K. (2026). The Silent Revolution of UPCT: The Birth of a New Physics to Thaw a Frozen World A Scientific Manifesto. Zenodo. https://doi.org/10.5281/zenodo.18439197 Ohumi, K. (2026). Civilizational Symmetry Breaking and the Pathology of Granulation under Strong Constraint Toward a Phase-Theoretic Account of Contemporary Crises. Zenodo. https://doi.org/10.5281/zenodo.18467976 Ohumi, K. (2026). From the Crystallized Self to the Generative Field Reclaiming the Observer's Perspective, the Ontological Value of Experience, and the Misalignment of Reason in Modernity. Zenodo. https://doi.org/10.5281/zenodo.18493557 Ohumi, K. (2026). Foundational Principles of Resonance Economics Reorienting Economic Theory from Output Maximization to Generative Sustainability. https://doi.org/10.5281/zenodo.18500861 Ohumi, K. (2026). Integration into the Life-OS Generativity Framework: Hokusai's The Great Wave off Kanagawa as an Ontological Model. https://doi.org/10.5281/zenodo.18505627 Ohumi, K. (2026). From Proof to Resonance: A Φ-Ontology of Existence, Labor, Education, and Economic Life. https://doi.org/10.5281/zenodo.18515955 Ohumi, K. (2026). Dialectics as a Relational Logic of Life: From Linear Ascent to Spiral Circulation. https://doi.org/10.5281/zenodo.18522371 Ohumi, K. (2026). Returning to the Source of Philosophy: Affirmation of Life as the Life-OS and a Radical Point of Departure. https://doi.org/10.5281/zenodo.18529485 Ohumi, K. (2026). Universal Phase Crystallization Theory (UPCT): The Pathology of Optimization and the Restoration of Generativity — Beyond Snapshot Ontology. https://doi.org/10.5281/zenodo.18597207
This article explores the role of zero-knowledge cryptographic proofs as a basic trust mechanism for financial and government digital services. The theoretical section explains how such proofs shift compliance verification from a "reveal data and verify" mode to a "prove property and admit access to service" mode, thereby reducing transaction costs, mitigating information asymmetries, and limiting agency costs. Drawing on insights from new institutional economics and mechanism theory, it demonstrates how formalized verifiability improves rule robustness, makes truthful reporting individually rational, and reduces the negative externalities of leaks. The analytical section systematizes classes of constructions, highlighting tradeoffs between proof size, latency, the need for trusted configuration, and operational risks. The practical section describes applications in payment infrastructure, lending, insurance, cross-border settlements, digital identity, and ledger management: range constraint verification, threshold and attribute verification, verifiable computation, and selective disclosure. It is demonstrated that with proper design, it is possible to combine data minimization with targeted transparency and effective enforcement, including in projects involving central bank digital money and pan-European identity wallets. Implementation metrics are discussed: marginal cost of proof and verification, average latency, fault tolerance, and the proportion of cases where primary documents are replaced with proof of property.
Shaoyu Li, Hexuan Yu, Shanghao Shi, Md Mohaimin Al Barat · 7 authors
With the growing demand for wireless spectrum, dynamic spectrum sharing (DSS) frameworks such as the Citizens Broadband Radio Service (CBRS) have emerged as practical solutions to improve utilization while protecting incumbent users (IUs) such as military radars. However, current incumbent protection mechanisms face critical limitations. The Environmental Sensing Capability (ESC) requires costly sensor deployments and remains vulnerable to interference and security risks. Alternatively, the Incumbent Informing Capability (IIC) requires IUs to disclose their identities and operational parameters to the Spectrum Coordination System (SCS), creating linkable records that compromise operational privacy and mission secrecy. We propose IU-GUARD, a privacy-preserving spectrum sharing framework that enables IUs to access spectrum without revealing their identities. Leveraging verifiable credentials (VCs) and zero-knowledge proofs (ZKPs), IU-GUARD allows IUs to prove their authorization to the SCS while disclosing only essential operational parameters. This decouples IU identity from spectrum access, prevents cross-request linkage, and mitigates the risk of centralized SCS data leakage. We implement a prototype, and our evaluation shows that IU-GUARD achieves strong privacy guarantees with practical computation and communication overhead, making it suitable for real-time DSS deployment.
Blockchain, while originally conceptualised to develop cryptocurrencies, may have broad applicational value across higher education. This study is the first scoping review to consider how blockchain has been used in healthcare higher education credentialling. It was designed using a Context-Input-Process-Product conceptual framework and adhered to PRISMA-ScR and JBI guidelines. The protocol was digitally registered [INPLASY2025120005] on 2nd December 2025, prior to the commencement of screening. EBSCO, Scopus and MEDLINE (Ovid) were searched using key terms related to healthcare, higher education, credentialling, and blockchain.Only five papers met all inclusion criteria, and the extant literature is predominantly theoretical. Public blockchain architectures were discussed however alternative private and consortium blockchains were underexplored despite possible sustainability, scalability, and privacy benefits. Only one paper discussed a governance model (autonomous self-governance). While ten themes of positive outcomes were theorised, no negative outcomes were posed and only one outcome (time efficiency) was empirically evidenced.This is a nascent field. Future research on blockchain-enabled should be based on advanced architectural modelling and evaluate governance and implementation strategies.
Nourhaine Nefzi, A. Melki, Sahar Loukil, Ahmed Jeribi
Abstract This study investigates the dynamic connectedness within the cryptocurrency market by analyzing four distinct cryptomarket blocks: Bitcoin and Ethereum (conventional cryptocurrencies); PAXG, DGX, and GLC (gold-backed cryptocurrencies); LINK and MNK (decentralized finance); and THETA and MANA (nonfungible tokens). Using the time-varying parameter quantile vector autoregressive (TVP-Quantile VAR) model for the period 2019–2023, our analysis reveals significant insights into the risk transmission dynamics among cryptocurrencies. Both conventional cryptocurrencies exhibit a consistent net transmitter effect in extreme periods, whereas decentralized finance (DeFi) and nonfungible tokens (NFTs) shift between a net shock transmitter and a net shock receiver over time and quantiles. Moreover, our results shed light on the hedging and safe haven properties of these assets. By linking the dynamic connectedness findings with established literature on hedging and safe haven functions, we elucidate how these cryptocurrencies perform under varying market conditions. Specifically, we report that the role of LINK, MNK, THETA, and MANA as reliable safe-haven assets is contingent upon the observed period. We also observe the hedge and safe haven properties of selected gold-backed cryptocurrencies within the network. Overall, our findings suggest that, despite the dynamic connectedness of the cryptocurrency market, investors have the flexibility to diversify across these digital assets.
Description of the Invention The present invention relates to the field of cybersecurity and artificial intelligence, and more particularly to a method and system for local autonomous internal penetration testing using artificial intelligence agents augmented by retrieval-based knowledge mechanisms. The invention discloses a technical solution in which one or more autonomous artificial intelligence agents operate within an internal enterprise environment to continuously assess the security posture of information systems, networks, services, and configurations. Unlike conventional penetration testing approaches that rely on manual effort, predefined scripts, or static rule-based scanners, the proposed system dynamically adapts its behavior based on observed system states, retrieved security knowledge, and learned experience. The system employs reinforcement learning to model penetration testing as a sequential decision-making problem, wherein an agent observes an environment state, selects an action from a defined action space, receives a reward based on the outcome, and updates its policy to maximize an expected cumulative reward associated with discovering security weaknesses, misconfigurations, or policy violations. The environment may include hosts, network topology, authentication mechanisms, access control rules, and security monitoring components. To overcome the limitations of fixed context windows and static knowledge in machine learning models, the invention integrates retrieval-augmented mechanisms. At each decision step, the agent retrieves relevant contextual information from a locally stored vector database containing embeddings of security documentation, vulnerability descriptions, configuration policies, compliance requirements, historical findings, and system metadata. The retrieval process is performed using approximate nearest neighbor search, enabling low-latency access to relevant knowledge at scale. The retrieved contextual data is used to augment the agent’s internal state representation and, in some embodiments, to construct augmented prompts for a local large language model responsible for high-level planning, reasoning, or task decomposition. This combination enables the agent to make informed decisions grounded in both learned behavior and up-to-date domain-specific knowledge. In certain embodiments, the system supports multiple cooperating agents, each specializing in a subset of penetration testing activities, such as reconnaissance, vulnerability identification, exploitation simulation, lateral movement analysis, or compliance auditing. Coordination between agents is achieved through a centralized planner or critic during training, while execution may occur in a decentralized manner. A key feature of the invention is that all data processing, retrieval, learning, and inference are performed locally within the organization’s infrastructure, without transmitting sensitive information to external systems. This design preserves confidentiality, complies with regulatory and organizational privacy requirements, and enables deployment in restricted or high-security environments. The disclosed method and system provide continuous, adaptive, and knowledge-informed internal security assessment, improving the detection of security weaknesses while reducing reliance on manual testing and static tools.
This study examines how Decentralized Autonomous Organisations (DAOs) could be incorporated into municipal administration to improve citizen participation and transparency. As DAOs in governance are attracting growing academic and practical attention, this research uses scenarios to analyze the conditions for their application at municipal and regional levels. It takes a conceptual, scenario-based approach to develop a model for DAO-based e-participation, identifying key concepts and their relationships to explain how DAOs operate as self-regulated systems for digital participation. The research is structured into three phases: First, in the foundational phase, this study synthesizes existing research on DAOs and participatory governance models, contrasting blockchain-based and traditional processes to establish a framework for DAO integration. Second, the application phase uses illustrative scenarios to explore how DAO mechanisms might influence participation and decision-making in municipalities. Third, the evaluation and recommendation phase consolidates insights into a structured model for implementation, highlighting task characteristics, contextual conditions, and organizational capacities that shape DAO feasibility. The analysis suggest that DAOs may enable new forms of participation and more transparent procedures, but only when antecedent conditions such as digital literacy, administrative capacity, and infrastructure stability are sufficiently met. Future work should look at long-term effects, compare cases across municipalities, and examine the role of legal and regulatory frameworks.
Anderson Melo de Morais, Fernando Lins, Nelson Souto Rosa
The Internet of Things (IoT) drives technological advances across various sectors by enabling seamless communication among smart devices. However, significant challenges remain regarding the integrity and reliability of the data stored by these devices. Traditional blockchain solutions, such as those based on Proof of Work (PoW), are generally unsuitable for IoT applications due to their high computational resource demands. Although approaches combining multiple consensus algorithms have emerged as alternatives to optimise performance and security, determining the best combination for each scenario remains an open problem. This paper proposes a strategy based on Genetic Algorithms (GAs) to adaptively select and combine consensus algorithms, thus improving blockchain efficiency in IoT environments. The approach was evaluated on a test blockchain, OmniBlock, implemented using a Directed Acyclic Graph (DAG) and designed specifically for evaluation purposes in IoT applications. OmniBlock supports multiple consensus algorithms, including Proof of Authority (PoA), Proof of Stake (PoS), Proof of Work (PoW), Practical Byzantine Fault Tolerance (PBFT), Raft, and others. The consensus algorithm combination is chosen based on performance attributes. All combinations of consensus algorithms evaluated in this work were suggested by GAs; the practical feasibility of each is analyzed empirically. Experimental results indicate that the evolutionary optimization-based strategy performs better across most of the combinations suggested by the GAs.
We present BAZINGA, a novel distributed system that achieves unification of artificial intelligence and blockchain through a new consensus mechanism called Proof-of-Boundary (PoB). Unlike traditional approaches that treat AI and blockchain as separate layers ("AI on blockchain"), BAZINGA demonstrates that AI and blockchain are Subject and Object of a single system, with consensus emerging from the boundary between them. The key discovery is that blockchain consensus can be achieved through understanding rather than computational work or financial stake. Nodes validate blocks by demonstrating comprehension via a mathematical boundary condition: the ratio of Physical to Geometric measures must equal φ⁴ ≈ 6.854 (where φ is the golden ratio). Key results: • 70 billion times more energy-efficient than Bitcoin • Sybil-resistant without financial stake • Unified with federated learning for distributed AI training • Validated through mathematical understanding rather than arbitrary computation The system includes four integration layers (Trust Oracle, Knowledge Ledger, Gradient Validator, Inference Market) that bind AI intelligence with blockchain validation. Fully implemented as open-source software (MIT License). Software: https://pypi.org/project/bazinga-indeed/ Source: https://github.com/0x-auth/bazinga-indeed Demo: https://huggingface.co/spaces/bitsabhi/bazinga
NFTs, kurz für Non-Fungible Tokens, sind digitale Zertifikate auf einer Blockchain, einer unveränderlichen Datenbank. Sie zeigen, wem ein digitales Objekt gehört, beispielsweise eine Grafik, Audio-Dateien, In-Game-Items oder Tweets. Anders als klassische Dateien, die beliebig kopiert werden können, dienen NFTs als Eigentumsnachweis. Die eigentliche Datei liegt meist auf externen Servern. NFTs sind Teil der Vision des Web3, eines dezentralen Internets, in dem Nutzer*innen über Inhalte, Besitz und digitale Identitäten selbst bestimmen sollen. Das Konzept eröffnet neue Möglichkeiten in virtuellen Welten, Spielen und Community-Projekten, stößt aber an Grenzen, weil Plattformen, Wallets und Anbieter letztlich entscheiden, wer teilnehmen darf. Bekannt wurden NFTs ab 2020 im Kunst- und Sammlermarkt, beispielsweise Beeples Everydays oder Sammlungen wie CryptoPunks. In Games und virtuellen Welten wie Axie Infinity oder Decentraland lassen sich Besitzrechte, Handelsmechanismen und Community-Dynamiken praktisch nachvollziehen. Nach dem anfänglichen Boom sank ab 2023 der Wert vieler NFTs, Plattformen verschwanden und technische wie rechtliche Fragen blieben offen. Für die Medienpädagogik bieten NFTs zahlreiche Ansatzpunkte: Fachkräfte können mit Lernenden über digitale Besitzformen, Wertzuschreibung, Marktmechanismen und soziale Dynamiken diskutieren. Eigene Experimente – Tokens erstellen, Sammlungen aufbauen, Spielobjekte gestalten – machen Logik, FOMO-Effekte und Machtstrukturen erfahrbar. Gleichzeitig lassen sich Nachhaltigkeit, langfristige Verfügbarkeit von Daten und Zugangshürden kritisch reflektieren. NFTs bieten so einen Einstieg, um digitale Wertlogiken, Teilhabe und Verantwortung im Web3 zu hinterfragen.
Censorship resistance is a core value of Web3, yet practical access to decentralized websites remains dependent on centralized gateways such as ipfs.io, .link, and .limo, which are susceptible to regulatory takedowns and availability limitations. This paper investigates the technical barriers to truly censorship-resistant access in decentralized web architectures and presents an engineering-driven analysis of dweb3.wtf, a dedicated rendering gateway developed within the Web3Compass infrastructure. The system directly interfaces with decentralized name systems such as ENS and Unstoppable Domains, autonomously resolves content hashes via on-chain resolvers, and renders the associated IPFS-hosted sites via self-hosted infrastructure. By eliminating reliance on third-party APIs and centralized frontends, the gateway offers a robust alternative to Web2-style intermediaries. This paper presents the architecture, implementation, and performance characteristics of dweb3.wtf, evaluating its effectiveness in ensuring access continuity, domain coverage, and reduced external dependency.
Samela Kivilo, Alex Norta, Marie Hattingh, Sowelu Avanzo · 5 authors
In recent years, tokenomic systems, decentralized systems that use cryptographic tokens to represent value and rights, have evolved considerably. Growing complexity in incentive structures has expanded the applicability of blockchain beyond purely transactional use. Existing research predominantly examines token economies within specific use cases, proposes conceptual frameworks, or studies isolated aspects such as governance, incentive design, and tokenomics. However, the literature offers limited empirically grounded, end-to-end guidance that integrates these dimensions into a coherent, step-by-step design approach informed by concrete token-economy development efforts. To address this gap, this paper presents the Token Economy Design Method (TEDM), a design-science artifact that synthesizes stepwise design propositions for token-economy design across incentives, governance, and tokenomics. TEDM is derived through an iterative qualitative synthesis of prior contributions and refined through a co-designed case. The artifact is formatively evaluated via the Currynomics case study and additional expert interviews. Currynomics is an ecosystem that maintains the Redcurry stablecoin, using real estate as the underlying asset. TEDM is positioned as reusable design guidance that facilitates the analysis of foundational requirements of tokenized ecosystems. The specificity of the proposed approach lies in the focus on the socio-technical context of the system and early stages of its design.
Allen Clement, Natacha Crooks, Neil Giridharan, Alex Shamis
Production state-machine replication (SMR) implementations are complex, multi-layered architectures comprising data dissemination, ordering, execution, and reconfiguration components. Existing research consensus protocols rarely discuss reconfiguration. Those that do tightly couple membership changes to a specific algorithm. This prevents the independent upgrade of individual building blocks and forces expensive downtime when transitioning to new protocol implementations. Instead, modularity is essential for maintainability and system evolution in production deployments. We present Gauss, a reconfiguration engine designed to treat consensus protocols as interchangeable modules. By introducing a distinction between a consensus protocol's inner log and a sanitized outer log exposed to the RSM node, Gauss allows engineers to upgrade membership, failure thresholds, and the consensus protocol itself independently and with minimal global downtime. Our initial evaluation on the Rialo blockchain shows that this separation of concerns enables a seamless evolution of the SMR stack across a sequence of diverse protocol implementations.
This thesis explores the doctrinal and practical challenges of applying the principle of party autonomy (lex voluntatis) to smart contracts and transactions governed by Artificial Intelligence (AI). The decentralized and immutable nature of Distributed Ledger Technology (DLT) fundamentally disrupts traditional private international law connecting factors, such as "place of performance" or "habitual residence." The author analyzes how the Rome I Regulation and the Hague Principles on Choice of Law can be adapted to "code-is-law" ecosystems where enforcement is automated and often bypasses state judicial mechanisms. Special attention is paid to the tension between algorithmic execution and "overriding mandatory provisions" (lois de police), questioning whether an AI can recognize and apply mandatory public policy norms that usually override the chosen law. The paper proposes a hybrid regulatory approach "Lex Cryptographia" that embeds choice of law clauses directly into the smart contract's metadata to ensure legal certainty.
Cryptocurrencies constitute a fast-evolving, disruptive technological development. Their proliferation and mainstreaming are undermining national security in several ways. By exploring emblematic cases, this paper examines how decentralised digital assets challenge sovereign functions, complicate law enforcement efforts, and give rise to security challenges. It explores different state-level responses to these developments by drawing on policy documents, reports, and guidance from multilateral regulatory authorities, alongside literature from finance, security studies, international relations, and technology governance. Strategic considerations spanning areas of illicit finance, sanctions evasion, great power rivalry, and state co-option by means of issuing Central Bank Digital Currencies and establishing cryptocurrency strategic reserves are delineated. A comprehensive mapping of the actual impact of cryptocurrencies across several strategic domains is carried out, synthesising insights from previously siloed technical, legal, and international relations literatures into an integrative national-security analytical lens. Specific recommendations are provided for policymakers and planners to navigate this fast-evolving threat landscape. • Synthesizes siloed literature to elucidate how Cryptocurrencies impact national security. • Cryptocurrencies are reshaping threat landscapes and emerging as a domain for great power competition. • Stablecoins strain monetary policy in fragile economies, while Privacy coins hinder AML/KYC enforcement and counter-terror efforts. • Sovereign actors are already using cryptocurrency to circumvent sanctions, fund weapon programmes and covert operations. • CBDCs seek to harness the benefits of cryptocurrencies while re-asserting sovereignty, reflecting divergent geopolitical strategies.
Energy poverty remains a critical barrier to socioeconomic development in rural Africa, where millions lack access to reliable electricity. This study explores the state of rural electrification, the consequences of dependence on traditional energy sources, and the potential of solar energy as a viable solution. Using a qualitative secondary research methodology, the study synthesizes data from scholarly articles, institutional reports, and case studies across various African nations, including Kenya, Rwanda, and Tanzania. Findings reveal that decentralized solar solutions, such as mini-grids and standalone solar home systems, offer scalable and cost effective alternatives to grid expansion. However, challenges such. Ydf as high upfront costs, weak regulatory frameworks, and limited financing mechanisms hinder widespread adoption. Innovative financing models, including pay-as-you-go (PAYG) schemes and microcredit financing, have demonstrated success in increasing energy affordability, while public-private partnerships (PPPs) have facilitated large-scale solar electrification projects. The study concludes that achieving universal energy access in rural Africa requires strengthened institutional support, policy harmonization, and increased investment in decentralized renewable energy solutions. Policy recommendations include government-led subsidy programs, tax incentives for solar enterprises, and enhanced regulatory frameworks to encourage private sector participation. This research contributes to the ongoing discourse on sustainable energy transitions by providing policy insights and strategic recommendations for accelerating rural electrification efforts in Africa.
The article provides a comprehensive study of the fundamental transformation of the nature of financial crises in the conditions of rapid digitalization of the global economy. It is shown that technological changes not only modify the toolkit of financial transactions, but also radically change the dynamics, speed and mechanisms of the spread of crisis phenomena. Special attention is paid to the evolution of banking panics: from traditional physical queues near branches to the phenomenon of "bank sprint", characterized by instantaneous, synchronized and mass withdrawal of liquidity through digital channels. This form of panic differs significantly from classical models in that the time lag between the appearance of negative information and the reaction of depositors is reduced from days or hours to minutes, which significantly complicates the possibilities of regulatory intervention. Based on historical analysis of the collapse of Continental Illinois (1984) and Silicon Valley Bank (2023), it is demonstrated that the digitalization of financial services combined with information synchronization through social networks creates conditions for an exponential acceleration of the spread of financial shocks. Particular attention is paid to new systemic risk vectors in the decentralized finance sector (DeFi), in particular the problem of the absence of automatic market fuses (circuit breakers) and threats of algorithmic cascading liquidations by smart contracts. The influence of artificial intelligence and large language models on market behavior, which contributes to the emergence of the "digital herding" effect, is considered. The need to change the regulatory paradigm is substantiated: the transition from static liquidity standards to dynamic management of operational stability. In this context, the unique experience of the Ukrainian Power Banking network was analyzed, which ensured the continuity of financial services in the conditions of large-scale crisis challenges caused by war and energy attacks. It is shown that the creation of a physically and energetically autonomous infrastructure of bank branches can be an effective tool for increasing the operational stability of the financial system.
This article examines the revolutionary impact of Artificial Intelligence (AI) on transforming cryptocurrency trading, a sector characterised by extreme volatility, dynamism, and nonlinear data. Through a rigorous bibliometric analysis based on the Web of Science database, this study examines a sample of 555 scientific papers published between 2016 and 2025, utilising the PRISMA protocol for systematic selection, and tools such as VOSviewer and MS Excel. The analysis identifies five major thematic clusters: (1) blockchain infrastructure and AI integration in decentralised ecosystems, (2) data analysis and practical applicability in crypto markets, (3) financial and social data analysis—machine learning algorithms, (4) algorithmic trading and automation, and (5) prediction and modelling of crypto market developments. The originality of this study lies in providing an overview of the implementation stage of these technologies by integrating the results into a map of Technology Readiness Levels (TRLs). The findings highlight a clear transition from traditional statistical methods to autonomous decision-making systems capable of processing massive volumes of data for portfolio optimisation. This study’s limitation is that it may require periodic updates, as the AI and cryptocurrency landscape are constantly evolving.
We show that a decidable promise problem has a non-interactive statistical zero-knowledge proof system if and only if it is randomly reducible via an honest polynomial-time reduction to a promise problem for Kolmogorov-random strings, with a superlogarithmic additive approximation term. This extends work by Saks and Santhanam (CCC 2022). (Saks and Santhanam showed that promise problems that can be reduced in this way to such an approximation of the Kolmogorov-random strings have (possibly interactive) zero-knowledge proof systems, and they did not address the converse implication.) We build on this to give new characterizations of Statistical Zero Knowledge SZK , as well as the related classes NISZK L and SZK L .