The advent of 5G networks has introduced a paradigm shift in communication infrastructure, facilitating ultra-low latency and high-speed data transmission. Despite this, this progress is accompanied by a spike in diverse and sophisticated cyberattacks, for which there is no comprehensive, foolproof defence strategy. In order to address the Scalability Trilemmaâachieving decentralization, scalability, and trustâand security concerns, this study proposes a robust security framework that combines blockchain technology with Zero Trust Architecture (ZTA). The proposed framework presents an end-to-end coherent workflow in four successive stages: (i) Access Request Initiation with contextual metadata, (ii) Decentralized identity verification via blockchain-based Decentralised Identifiers (DIDs) and Verifiable Credentials (VCs), (iii) Context-aware Dynamic Access Control enforced through smart contracts, risk scoring, and cryptographic mechanisms such as Zero Knowledge Proofs (ZKPs) and Multi-Factor Authentication (MFA), and (iv) Time-bound, least-privilege access provisioning with continuous session monitoring and immutable logging. The model, which is proposed to be strategically implemented at the 5G network's device (access) layer, affirms real-time enforcement while maintaining accountability, privacy, and verifiability. Our research delivers a fully decentralized, tamper-resistant, and scalable architecture capable of dynamically mitigating advanced cyber threats, while ensuring secure delivery of 5G services across diverse use cases.
The increasing penetration of intermittent renewable energy demands innovative solutions to maintain grid stability, resilience, and security in the body of smart cities. This paper presents a novel framework that redefines Bitcoin mining as a form of virtual energy storage, a flexible and controllable load capable of delivering large-scale demand response services, positioning it as a competitive alternative to traditional energy storage systems, including electrical, mechanical, thermal, chemical, and electrochemical storage solutions. By strategically aligning mining activities with grid conditions, Bitcoin mining can absorb excess electricity during periods of oversupply, converting it into digital assets, and reduce operations during times of scarcity, effectively emulating the behavior of conventional energy storage systems without the associated capital expenditures and material requirements. Beyond its operational flexibility, this paper explores the cyberâphysical benefits of integrating Bitcoin mining into the power transmission systems as a defensive mechanism against false data injection (FDI) cyberattacks in smart city infrastructure. To achieve this goal, a decentralized and adaptive control strategy is proposed, in which mining loads dynamically adjust based on authenticated grid-state information, thereby improving system observability and hindering adversarial efforts to disrupt state estimation. In addition, to handle the proposed approach, this paper introduces a high-performance algorithm, a combination of quantum-augmented particle swarm optimization and wavelet-oriented whale optimization (QAPSO-WOWO). Simulation results confirm that strategic deployment of mining loads improves grid sustainability by utilizing curtailed renewables, enhances resilience by mitigating load-generation imbalances, and bolsters cybersecurity by reducing the impacts of FDI attacks. This work lays the foundation for a transdisciplinary paradigm shift, positioning Bitcoin mining not as a passive energy consumer but as an active participant in securing and stabilizing the future power grid in smart cities.
The enactment of the Nigeria Tax Act (NTA) 2025 represents a significant restructuring of the nationâs fiscal framework, aimed at capturing value within the borderless digital economy. This study provides a legal analysis of the updated "Significant Economic Presence" (SEP) rule under Section 17 of the Act, which shifts the taxable nexus from traditional physical presence (Permanent Establishment) to economic participation. By expanding the SEP framework, the NTA 2025 formalises the "digital shadow" of the workforce, explicitly including remote freelancers, digital consultants, and content creators within the tax net while mandating residency-based taxation on worldwide income. Additionally, the Act classifies profits from digital asset transactions, including cryptocurrencies and non-fungible tokens (NFTs), as taxable income. The analysis also examines the institutional transition from the Federal Inland Revenue Service to the Nigeria Revenue Service (NRS), emphasising the deployment of automated technologies for real-time reporting and collection. Despite these advancements, persistent challenges remain, including infrastructure deficits, enforcement complexities in peer-to-peer transactions, and the need to align with global standards such as the OECDâs Two-Pillar Solution. Ultimately, the study concludes that although the NTA 2025 modernises the fiscal social contract, its effectiveness in optimising revenue depends on institutional capacity and clear regulatory guidance.
Matteo Vaccargiu, Sabrina Aufiero, Silvia Bartolucci, Ronnie de Souza Santos ¡ 6 authors
Labels on platforms such as GitHub support triage and coordination, yet little is known about how well they align with code modifications or how such alignment affects collaboration across contributor experience levels. We present a case study of the Kubernetes project, introducing label-diff congruence - the alignment between pull request labels and modified files - and examining its prevalence, stability, behavioral validation, and relationship to collaboration outcomes across contributor tiers. We analyse 18,020 pull requests (2014--2025) with area labels and complete file diffs, validate alignment through analysis of over one million review comments and label corrections, and test associations with time-to-merge and discussion characteristics using quantile regression and negative binomial models stratified by contributor experience. Congruence is prevalent (46.6\% perfect alignment), stable over years, and routinely maintained (9.2\% of PRs corrected during review). It does not predict merge speed but shapes discussion: among core developers (81\% of the sample), higher congruence predicts quieter reviews (18\% fewer participants), whereas among one-time contributors it predicts more engagement (28\% more participants). Label-diff congruence influences how collaboration unfolds during review, supporting efficiency for experienced developers and visibility for newcomers. For projects with similar labeling conventions, monitoring alignment can help detect coordination friction and provide guidance when labels and code diverge.
This paper explores the relationship between fiscal decentralization, green finance, and the digital economy in driving sustainable development, using a balanced cross-country panel dataset spanning 2014â2022, for 29 European countries. Employing dynamic panel estimation techniques, including system generalized method of moments (GMM), the research investigates how fiscal decentralization, green finance, and the digital economy (each of them individually and through interaction mechanisms), dynamically shape sustainable development performance in the presence of endogeneity and temporal persistence. The findings reveal strong inertia in sustainable development, which depends on its previous level. Fiscal decentralization has complex effects: revenue autonomy supports sustainability, whereas expenditure autonomy may undermine it, suggesting differences in how resources are used efficiently at the local versus central levels. Digitalization acts as a catalyst, boosting the effectiveness of environmental taxes and enhancing local spending outcomes. However, if fiscal administrations are not digitally integrated, digitalization may weaken the benefits of decentralized revenues. This study advances the literature by integrating fiscal, financial, and digital views, providing new insights into policy coordination.
Decentralized Finance (DeFi) operating in Benin are essential for financing the agricultural sector and for achieving the Sustainable Development Goals. This research contributes to the debate on the effectiveness of agricultural financing models proposed by DeFi in Northern Benin. Two theoretical approaches are mobilized to assess farmersâ perceptions : Triandisâ interpersonal behaviour model (1979) and the balanced incomplete block design method for analyzing farmersâ choices. A total of 585 farmers were surveyed, including 385 financing beneficiaries, using purposive sampling. Data were analyzed with R version 4.3.0 and RStudio version 2022.02.0. The results highlight a preference for individual financing models (61.26%) over group-based models (38,74%), as they better meet the immediate needs of farmers. Regarding the impact of financing models on agricultural factors of production, farmers acknowledge the positive effect of individual financing on the purchase of inputs and equipment, but criticize the inability of group financing models to stimulate overall productivity and land expansion. The overall perception of support systems implemented after financing is negative, as they remain disconnected from farmerâs real needs. It therefore appears that while financing models satisfy beneficiaries in terms of immediate operational aspects (inputs, equipment, financial needs), and they fail to address structural expectations such as productivity growth and farmland expansion
Blockchain technology is often discussed as if it emerged from nowhere, yet its architectural DNA traces directly to the decentralized computing principles James~N. Gray articulated in 1986. This paper maps the conceptual lineage from Gray's requestor/server model to modern blockchain architectures, showing how his emphasis on modularity, autonomy, data integrity, and standardized communication anticipated the design of systems like Bitcoin and Ethereum, and, more recently, the Web3 movement and Layer-2 scaling architectures. We examine consensus mechanisms, cryptographic foundations, rollup-based Layer-2 protocols, and cross-chain interoperability through this historical lens, identify persistent challenges in scalability and modularity, and outline future directions toward Web4: an intelligent, decentralized internet integrating blockchain, artificial intelligence, and the Internet of Things.
Web3 authentication stacks largely inherit ECDSA centric single-signature workflows that limit security and efficiency, while custody of identity data often remains application controlled rather than self-sovereign. We present S-Auth, an authentication layer that combines BIP340 Schnorr signatures with Decentralized Identifiers (DID), Verifiable Credentials (VC), and Content addressing (CID). The proposed solution utilizes Schnorr digital signatures, which have demonstrated improved security and efficiency over traditional schemes. The contributions of this work are as follows. Firstly, we apply the BIP340 standard to Schnorr digital signatures, bolstering security against various attacks including strong unforgeability under chosen message attack (SUF-CMA), non-malleability, linearity, related-key at tacks, hash collision, fault injection, nonce exfiltration, resource exhaustion, and domain separation. Secondly, we leverage the linearity property of Schnorr signatures to enable multi-signature aggregation and batch verification, addressing the inefficiency of existing schemes that rely on single signatures and thereby also enhancing privacy. Third, we combine the blockchain with DID, VC, and IPFS to provide a secure and self-sovereign identity that can be authenticated. Experiments comparing ECDSA, Ed25519, Schnorr, and BIP340 show that S-Auth reduces signature artifacts via aggregation, improves verifier throughput with batching, and decreases anchoring overhead while preserving user-controlled identity. S-Auth provides a self-sovereign, efficient, and secure authentication mechanism suitable for Web3 environments.
Autonomous AI agents increasingly execute consequential actions against operational infrastructure. This paper presents AEGIS, a constitutional governance architecture that enforces deterministic policy at the agent action boundary â post-reasoning, pre-execution. AEGIS satisfies Anderson's reference monitor properties, aligns with all four functions of the NIST AI Risk Management Framework, and introduces a decentralized federation model for cross-organizational governance intelligence sharing. Submitted to IEEE Computer, Special Issue on AI Governance and Compliance.
The amount of international capital invested in sustainability-focused investments and decentralized financial technologies has been growing fast. Thus, this research focuses on the transmission of volatility and optimal portfolio composition among decentralized finance (DeFi) assets, S&P renewable energy and technology market indices, and conventional energy commodities for the period from March 15, 2018, to August 30, 2024. The sample period was divided into three sub-periods to examine the impact of COVID-19, which increased in parallel with the adoption of DeFi and a focus on sustainability: pre-COVID, during-COVID, and post-COVID. This research utilizes the Diebold-Yilmaz and BarunĂk-KĹehlĂk techniques for time-and frequency-domain analyses, and the Dynamic Conditional Correlation model for portfolio optimization. First, the findings reveal that DeFi tokens (sustainable markets) (brown investments) display moderate (high) (very low) internal connectedness. Second, DeFi tokens demonstrate very low volatility connectedness with both sustainable and brown markets, which suggests strong diversification effects. Third, volatility connectedness among sustainable markets and conventional energy commodities is equally low. Fourth, sustainable markets (conventional energy commodities) make the highest (lowest) contribution to total volatility connectedness, and they operate as net transmitters (receivers) of volatility. Moreover, the total volatility connectedness is 33.7%, which is relatively low, suggesting significant opportunities for diversification of investment portfolios. Furthermore, the outcomes for optimal portfolio weights present greater allocations to green markets compared to conventional energy commodities and DeFi assets, revealing an escalating global transition toward sustainability. Additionally, COVID-19 significantly influenced volatility transmissions and portfolio allocations.
Multi-chain ecosystems suffer from fragmented identity, siloed liquidity, and bridge-dependent token transfers. We present n-VM, a Layer-1 architecture that hosts n heterogeneous virtual machines as co-equal execution environments over shared consensus and shared state. The design combines three components: a dispatcher that routes transactions by opcode prefix, a unified identity layer in which one 32-byte commitment anchors VM-specifific addresses, and a unified token ledger that exposes VM-native interfaces such as ERC-20 and SPL over a common balance store. We formalize routing, identity derivation, and token transfer semantics, and prove cross-VM transfer atomicity and identity isolation under standard cryptographic assumptions. We describe a concrete instantiation with five VMs: a native runtime, EVM, SVM, Bitcoin Script, and TVM. We also present context-based sharding and a write-set scheduler for parallel execution. Under an analytical throughput model, the architecture admits a projected range of about 16,000 to 66,000 transactions per second on commodity hardware.
Stablecoins serve as the fundamental infrastructure for Decentralised Finance (DeFi), acting as the primary bridge between fiat currencies and the digital asset ecosystem. While peg stability is well-documented, the structural role stablecoins play in transmitting systemic risk to the broader market remains under-explored. This study uses copula-based approaches to quantify the transmission of volatility and activity from stablecoin to cryptocurrency markets. We demonstrate in-sample causality across daily, weekly, and monthly horizons. Furthermore, we show that incorporating stablecoin factors significantly reduces Mean Squared Error in cryptocurrency forecasting. Specifically, we link stablecoin volume and upside volatility to broader market volatility, indicating its role as dry powder. Finally, we establish economic value by demonstrating reduced risk in a cryptocurrency volatility targeting model when stablecoin factors are employed.
<div> Large Language Models (LLMs) are transforming 1 blockchain security and analytics, yet a system-2 atic evaluation of their capabilities remains limited. 3 This survey provides a comprehensive, AI-centric 4 assessment of LLM-based methods across over 70 5 recent studies spanning 11 application domains, 6 such as security auditing, transaction fraud de-7 tection, and cryptocurrency portfolio management. 8 Our unified taxonomy standardizes task formula-9 tions and evaluation practices to enable a com-10 parison of six LLM roles across domains. For 11 each domain, we review input representations tai-12 lored to blockchain data; LLM architectures, learn-13 ing and inference paradigms, e.g., fine-tuning, 14 retrieval-augmented generation, and agentic strate-15 gies. Our review analyzes the strengths, limita-16 tions, and emerging patterns of LLM roles observed 17 in current systems. Finally, we provide practi-18 cal guidance for selecting LLMs for specific roles 19 and outline promising research directions. The on-20 line resources of this survey are available on https: 21 //llmblockchain.github.io/LLMBlockchain/. 22 1 Introduction 23 Large Language Models are increasingly incorporated into 24 blockchain systems for both security and financial analyt-25 ics, including smart contract auditing, transaction monitoring, 26 fraud detection, market analysis, and decentralized finance 27 </div>
Password-based authentication systems remain the most widely used method for user verification despite being highly susceptible to offline dictionary attacks. To mitigate such attacks, server-aided password-based authentication schemes utilize an independent server, which helps to harden the credentials to be stored on the website database. Existing server-aided password-based authentication schemes rely on number-theoretic assumptions that are vulnerable to quantum-enabled adversaries and incorporate complex computations such as bilinear pairings, exponentiation, and Zero-Knowledge Proofs. In this work, we introduce a novel post-quantum secure server-aided password-based authentication scheme based on the Module Learning With Errors (M-LWE) problem. A defining feature of our protocol is its complete operational transparency as it integrates with existing web interfaces without requiring users to modify their login behaviour or perform additional computation. To ensure long-term resilience, our scheme includes a transparent key rotation mechanism that allows service providers to update the entire credential database with a fresh secret key without user intervention. We provide a formal security analysis in the Real-or-Random (RoR) framework. This analysis demonstrates that our protocol's resistance to offline dictionary attacks reduces to the underlying hardness of the M-LWE problem, and the system achieves forward secrecy through a key rotation mechanism. Through an optimized Number Theoretic Transformation (NTT)-based implementation for faster polynomial multiplications, our empirical analysis demonstrates high computational efficiency, with average registration and authentication latencies of 0.88 ms and 0.96 ms, respectively.
Current mobile System-on-Chip (SoC) architectures suffer from a fundamental âReactive Polling Tax,â where high-level software must frequently interrupt low-power hardware states to query rawsensor telemetry. This paper introduces the Contextual Neural Bus (CNB), a dedicated, asynchronous hardware-level interconnect designed to shift context awareness from volatile software cycles to deterministic silicon logic. By utilizing a decentralized multi-modal fusion layer, the CNB generates Universal Intent Tokens (UITs)â64-bit cryptographic primitives that represent verified user states at the physical layer. Unlike legacy co-processors that merely buffer data, the CNB integrates a Hardware-Resident Zero-Knowledge Proof (ZKP) Generator to provide mathematical certainty of user intentwhile physically isolating raw biometric and environmental telemetry within a secure silicon enclave. Preliminary simulations using a digital-twin SoC model indicate a 90.8% reduction in interrupt driven power consumption, effectively achieving âEnergy-Neutral Privacyâ by utilizing the resulting power surplus to offset cryptographic overhead. Furthermore, the architecture introduces Predictive L3 Cache Pre-warming, which anticipates user interactions to virtually eliminate âcold-startâ application latencies. By anchoring proactive computing in the deterministic reliability of silicon, this work establishes a scalable, privacy-first path toward zero-latency, energy-autonomous mobile ecosystems.
As collaborative work increasingly incorporates artificial intelligence, accurately identifying and attributing human contributions across teams has become a critical challenge. Traditional attribution methods rely on output-based metrics or narrative reconstruction, both of which fail to capture the underlying intellectual contributions that drive outcomes. This work introduces the Team Contribution Attribution Ledger (TCAL), a framework for aggregating distributed Human Conception Ledger (HCL) records to generate structured, evidence-based attribution across collaborators. TCAL synthesizes individual human-origin contribution events into team-level attribution models, enabling quantifiable yet human-reviewed determination of contribution. The framework provides a scalable system for attribution in research, engineering, and organizational environments, supporting applications in intellectual property, authorship, compensation, and governance.Related to Human Conception Ledger:Human Conception Ledger (HCL): A Framework for Provenance, Attribution, and Human Inventorship in AI-Augmented Systems
Since World War II, the US dollar (USD) has substantially increased its prominence in international financial systems, culminating in its position as the predominant currency, facilitating approximately 90% of global foreign exchange transactions. The reliance of most nations on the USD for international trade - particularly for oil, commodities, and other goods - has cemented its critical role in global finance and geopolitics. Hence, the usage of the USD supported and forged an economic and geopolitical function for the emitting country, the United States of America. The geopolitical implications and risks related to the USD hegemonic power in trade and financial transactions have become increasingly more striking, especially in recent decades and years. The sanctions imposed on Venezuela, Iran and more recently on Russia via the US dollar-dominated SWIFT payment system highlighted the potential threat posed by the USD hegemonic power in the global monetary system. However, in the new millennium, alternative digital currencies have begun to exert influence and have implicitly and explicitly posed a threat to that hegemony. Bitcoin and other cryptocurrencies, for instance, have enabled international transactions without reliance on USD use. Additionally, the emergence of several multi-currency Central Bank Digital Currencies (CBDCs) would allow nations to conduct cross-border payments using various currencies without passing through the USD as an intermediary. Our paper explores the geopolitical implications of USD use on the international stage and examines the potential opportunities and threats posed by these new digital currencies for countries.
Peer-discovery protocols within P2P networks are often vulnerable: because creating network identities is essentially free, adversaries can eclipse honest nodes or partition the overlay. This threat is especially acute for blockchains, whose security depends on resilient peer connectivity. We present AetherWeave, a stake-backed peer-discovery protocol that ties network participation to deposited stake, raising the cost of large-scale attacks. We prove that, with high probability, either the honest overlay remains connected or a $(1{-}δ)$-fraction of nodes in every smaller component raise an attack-detection flag -- even against a very powerful adversary. To our knowledge, AetherWeave is the first peer-discovery protocol to simultaneously provide Sybil resistance and privacy: nodes prove they hold valid stake without revealing which deposit they own, and gossiping does not expose peer-table contents. A cryptographic commitment scheme rate-limits discovery requests per round; exceeding the limit yields a publicly verifiable misbehavior proof that triggers on-chain slashing. Beyond deposit and slashing, the protocol requires no on-chain interaction, with per-node communication scaling as $O(s\sqrt{n})$. We validate our design through a mean-field analysis with closed-form convergence bounds, extensive adversarial simulations, and an end-to-end prototype built by forking Prysm, a leading Ethereum consensus client.
This research article examines how distributed ledger technology (DLT) can enhance modern-day economies and the mechanisms that enable this emerging technology to sustain them in the long term. The mission of this study is to educate a diverse group of economic leaders, encompassing government agencies and private companies, about DLT and its potential to shape the future. This study analyzes secondary qualitative data to show that DLT can enhance and sustain economies in multiple ways, specifically through the three pillars of modern-day economies: central banks, commercial banks, and land registry systems. More specifically, the architectural mechanisms of DLT reduce moral hazard arising from centralized economic authorities, increase the efficiency of financial services and money movements, and lower the costs of financial services that can be passed on to consumers. Further benefits include the creation of new jobs, new industries, a new asset class, and renewed industries through the adoption of this new infrastructure, thereby expanding markets by building strong foundations for economies to grow through immutable land records, and building trustless networks worldwide.
Based on the graphic novel DalĂ's Mustache and Other Colors, published by Polirom in 2020, the article DalĂ's Mustache between Color, Word, Image, Non-Fungible Token, and... Sound proposes a reevaluation of the concept of musicological research from a contemporary interdisciplinary perspective, as an authentic act of culture. The 16 paintings imagined by visual artist Felix Aftene, perfectly suited to the equally impressive literary chapters written by Lucian Dan Teodorovici, follow a path marked by metamorphosis, with stops that generate new meanings and senses (video artist Andrei Cozlac, Blockchain consultant Gabi Dumitru), with the final destination being the concert stage in the orchestral suite composed by the young musician Paul Pintilie and premiered at the Classix Festival in 2023 on the stage of the âVasile Alecsandriâ National Theater in IaČi, performed by the National Youth Orchestra of Moldova and the âSonos Alumniâ Chamber Orchestra of the IaČi University of Arts. The article is conceived along parallel lines/arts, but continuously linked by a common thread: DalĂ's moustache, a surrealist universe in which the conventional-unconventional dualism fits perfectly.
Antonio Roberto Xavier, GILSON ADĂO DOMINGOS VIEIRA, Fidel Cambundo Sanuca, Edmilson Alberto Matamba ¡ 8 authors
The main objective of this work is to investigate the level of cooperation, decentralization, and dialogue that exists between municipalities due to the federal pact. The 1988 Federal Constitution established the federal pact with a peculiarity: the so-called triune federalism, which recognizes the existence of three federative entities: the Union, the states, and the municipalities. Municipalities possess their own political, administrative, and financial competencies, but this decentralization also entails serious problems. Municipalities are autonomous, but many of them do not produce enough to sustain and develop themselves, and often municipal, state, and federal responsibilities are confused with the implementation of the National Education System. By the end of 2025, this scenario had changed, with the creation of a clear document outlining what each entity should do. This was linked to the new Fund for the Maintenance and Development of Basic Education and the Enhancement of Education Professionals, officially made permanent in 2020, and the mass participation in Education Development Arrangements and municipal public consortia, which led to a significant improvement in the Basic Education Development Index of several municipalities. From a methodological point of view, a Bibliographic and Documentary Review was used, this being a quantitative-qualitative research, of a basic nature and of a theoretical genre. The main results show that cooperation between municipalities is indispensable for public policies to take place and achieve their objectives based on the federative pact, since, as demonstrated; many municipalities have improved in development, especially regarding economies of scale applied to education.
On-chain lending has expanded across multiple distributed ledgers as DeFi becomes increasingly multi-chain. This environment introduces novel technical and financial mechanisms, particularly cross-blockchain communication and asset transfer protocols, yet cross-chain elements remain understudied in lending protocol risk management. To address this gap, we applied panel regression fixed effects and OLS models to empirically analyze cross-blockchain interoperability solutions, using TVL and total revenue as performance proxies from October 2022 to January 2025. Our data set covers 15 decentralized lending protocols and 53 cross-chain bridges across 9 EVM-compatible blockchains, categorized as Ethereum, alternative layer-1s, and Ethereum layer-2 networks. Results reveal that cross-chain activity impacts on protocol performance. Bridge volume emerges as a critical driver, exerts a significant effect on TVL and revenue across different categories, though the direction of this effect varies heterogeneously. Increased bridge integrations are associated with decreased TVL and protocol revenue across categories, indicating liquidity escapes from those lending ecosystems. Liquidations produce heterogeneous effects across categories. New network launches do not have as significant relationships with TVL and revenue while bridge hacks show a significant and positive relationship. High R-squared values confirm meaningful explanatory power. We further show Ethereum attracts large depositors, while layer-2s skew toward retail participation. We conclude that effective DeFi risk models should incorporate cross-chain metrics and adopt a layer-aware approach to accurately reflect the evolving multi-chain landscape.