P Praveen Kumar, Dudimetla Pravalika, B. S. Dileep Kumar, Gattu Akshitha · 5 authors
The rapid advancement of blockchain technology has introduced new possibilities for secure digital ownership and transparent fundraising through Non-Fungible Tokens (NFTs).However, most existing charity platforms remain centralized, limiting transparency, accountability, and verifiable proof of donations.Donors often lack visibility into how funds are utilized, while reliance on intermediaries increases risks such as data manipulation, reduced auditability, and decreased trust.To address these issues, this work proposes a decentralized charity auction framework that leverages blockchain technology and NFT-based asset representation.The system is developed using the Django web framework integrated with Web3 infrastructure and smart contracts.In this model, each auction item is tokenized as a unique NFT, ensuring authenticity, traceability, and immutable ownership.The platform allows users to act as donors or auctioneers, enabling participation in NFT-based charity auctions.Users can place bids or contribute funds, with all transactions securely recorded on a blockchain ledger.At the end of each auction, NFT ownership is automatically transferred to the highest bidder or contributor, providing verifiable proof of participation.By removing intermediaries and incorporating a transparent, incentive-driven mechanism, the proposed system enhances donor trust and engagement.It ensures tamper-proof record-keeping and clear fund flow, strengthening accountability within charitable ecosystems.This framework demonstrates a scalable and efficient approach to modern fundraising, showcasing the potential of blockchain and NFTs in improving trust and transparency in charity applications.
ONU 2.0 is a next-generation global governance platform designed to coordinate publicpolicy, development projects, and multilateral philanthropy across BRICS+ member statesand international observer partners. Built on a hybrid architecture that combines traditionale-government systems with Web3 infrastructure and distributed artificial intelligence, itimplements a complete workflow of submission → GPS jurisdictional validation → multi-levelapproval pipeline → audited execution → on-chain anchoring.At the technical level, the platform is structured around seven architectural layers: GPSjurisdictional control, multi-level approval state machines, asynchronous message routing (AOprotocol), cryptographically chained audit ledgers, BRICS+ policy exchange, BitcoinOP_RETURN anchoring via Arkhe-Chain (Chain ID 2140), and Kuramoto oscillator-basednetwork coherence consensus. The AI module is implemented as a Bittensor fork — the ONU2.0 Subnet — with six specialized sub-networks for data validation, policy enforcement, auditsurveillance, subnet mining, sovereign identity, and ethical oversight.Philosophically, ONU 2.0 is grounded in the C/Z duality of the Arkhe(n) framework:governance as the projection of the field of possibility (C-domain: policy intent, legal norms,stakeholder consensus) into the field of actuality (Z-domain: executed transactions,immutable audit records, on-chain commitments). The Kuramoto coherence layeroperationalizes this philosophical premise — network governance achieves legitimacy whenthe synchronization of operator nodes crosses the critical threshold phi_c = 0.618.
Healthcare AI systems put a lot of importance on keeping medical data private because it is very sensitive. AI-driven diagnostic models could help doctors make better decisions, but they need a lot of different patient data sets, which are often kept separate from each other at different hospitals. Federated Learning (FL) is a decentralised way to solve this problem by letting multiple people train a model together without sharing data in one place. But conventional FL frameworks continue to encounter challenges related to trust, transparency, and data integrity. This paper puts forth a Blockchain-Enabled Federated Learning Framework to facilitate secure, privacy-preserving, and auditable medical diagnosis across decentralised healthcare systems. This system uses blockchain's unchangeable nature and smart contract features to make sure that model updates can't be changed, contributions can be tracked, and trust between the entities involved is higher. This combination makes AI-driven diagnostics possible without putting patient privacy, regulatory compliance, or institutional integrity at risk.
Traditional digital card games rely on centralized servers, introducing catastrophic single points of failure, while decentralized Web3 alternatives fail to achieve real-time viability due to prohibitive block latency. This paper introduces Panoptes, an optimized, hybrid cryptographic engine that enforces low-latency decentralized consensus for peer-to-peer state channels. Assuming a highly hostile user-space environment, Panoptes treats the host application space and its underlying managed runtime as fundamentally compromised.A bifurcated architecture is detailed utilizing a hardened native airgap and direct OS-level memory mapping to process ciphertexts, bypassing standard and predictable libc allocators. To mitigate automated memory scrapers and frustrate asynchronous Direct Memory Access (DMA) attacks, Panoptes implements a multiplexed decoy memory topology (The Vault). This architecture relies on strict virtual page guarding, offline decryption, and temporal starvation via millisecond-scale execution windows. The protocol replaces commutative encryption with a deterministic Hand Commitment Payload, utilizing X25519 KEM, XOR- based Secret Sharing, and ChaCha20-Poly1305 to enforce Strict Zero-Trust Consensus.
Traditional digital card games rely on centralized servers, introducing catastrophic single points of failure, while decentralized Web3 alternatives fail to achieve real-time viability due to prohibitive block latency. This paper introduces Panoptes, a highly optimized, hybrid Zero-Trust cryptographic engine that enforces microsecond-latency decentralized consensus for the CoronaPoker peer-to-peer network. Assuming a strict Ring-0 adversary model, Panoptes treats the host operating system and the Java Virtual Machine (JVM) as fundamentally compromised. We detail a bifurcated architecture utilizing a hardened native airgap that leverages OS-level stealth allocators to process ciphertexts without leaving plaintext residue in the managed heap. To mitigate OS-level memory scrapers and hardware-based Direct Memory Access (DMA) attacks, Panoptes implements a multiplexed decoy memory topology (The Vault). It is secured by strict virtual page guarding against software introspection, and heavily relies on offline decryption with immediate sub-millisecond zeroization to temporally starve asynchronous hardware-level carving. The protocol entirely replaces traditional commutative encryption with the deterministic Hand Commitment Megapacket, a flat-buffer payload leveraging X25519 KEM, Additive Secret Sharing, and ChaCha20-Poly1305 to ensure Byzantine fault tolerance without majority voting. We present formal implementations of our micro-architectural defenses, including Mixed Boolean-Arithmetic (MBA) for constant-time execution, direct cross-platform syscalls bypassing libc, OS-level DACL lockdowns, PEB cloaking, and asynchronous SipHash-2-4 binary attestation. Furthermore, we introduce a multithreaded Deadman Switch to detect CPU cycle drift via RDTSC. Evaluated under an exhaustive 42-point "Total Siege" adversarial framework, the engine demonstrates unparalleled resilience against hardware breakpoints, kernel introspection, inline hooking, and temporal drift attacks.
В статье изучается, как технологические прорывы, в частности блокчейн и искусственный интел-лект, трансформируют краудфандинг в контексте цифровой перестройки финансовых рынков. Особое вниманиеуделяется тому, как эти технологии формируют современную краудфандинговую среду. Исследование демонстри-рует, что применение смарт-контрактов, инструментов анализа больших данных и систем цифровой идентифи-кации повышает прозрачность, минимизирует риски для инвесторов и укрепляет доверие между пользователямиплатформ. Рассматривается эволюция краудфандинга от классического коллективного финансирования к децен-трализованным финансовым моделям, таким как Web3, DeFi, токенизация активов и DAO. Подчеркивается, чтоинтеграция финтех-решений создает новую парадигму инвестирования, основанную на автоматизации, децентра-лизации и цифровой инфраструктуре. В заключение делается вывод, что дальнейшее развитие краудфандингабудет напрямую зависеть от технологических достижений и их интеграции в финансовые экосистемы
The digital art and collectibles industries are undergoing a significant transformation due to a phenomenon known as Non-fungible Tokens (NFTs). Enabled by smart contracts on a blockchain, NFTs thus provide creators with unparalleled control. They can be used to indicate the ownership of any unique object by serving as a deed for that item, whether it exists in the physical or digital world. This research aims to shed light on various obstacles to the widespread adoption of NFTs. A semi-structured interview was conducted with customers of NFT marketplaces to draw out valuable insights across diverse scenarios. The interview method has been utilized to observe and assess the perspectives of individuals who have engaged in marketplace transactions. Furthermore, a cognitive walkthrough was executed to evaluate the marketplace’s usability from a newcomer’s viewpoint. The insights gathered from the interviews and cognitive evaluation have pinpointed significant pain points and opportunities for improvement. The findings show that both experienced users and newcomers are seeking enhancements to the marketplaces before they are willing to embrace this technology on a larger scale. Their recommendations vary from ensuring safer ecosystem development to improving user interfaces. We present a review of our findings from multiple angles, addressing areas where challenges are evident and we suggest potential modifications to boost the promotion of NFTs. In conclusion, based on our results, we recommend an ideal design along with several essential strategies akin to other standard applications that could be implemented in the markets for greater acceptance.
The rapid expansion of the digital ecosystem has introduced pressing challenges surrounding identity, authenticity, trust, and transparency. The ease with which digital content can be duplicated often undermines creators, whose works are distributed without consent or fair compensation. Blockchain technology offers a transformative solution through its decentralized, transparent, and tamper-resistant structure. Among its innovations, non-fungible tokens (NFTs) provide a mechanism to verify the authenticity and ownership of unique digital assets. This study explores the transformative potential of NFTs in strengthening digital ownership and authenticity while identifying critical challenges such as market concentration, interoperability limitations, and security vulnerabilities within public NFT platforms. Employing the extreme programming (XP) methodology, this research proposes a secure framework for NFT creation outside public marketplaces to enhance the protection of smart contracts and user accounts. The findings demonstrate that this approach grants users’ greater control, minimizes exposure to platform-level risks, and promotes trust in decentralized asset management. Overall, this study underscores NFTs’ pivotal role in reshaping digital ownership models and highlights the need for continued innovation to ensure security, transparency, and equitable value distribution in the evolving digital economy.
On high-throughput, low-fee blockchains, a qualitatively new form of maximal extractable value (MEV) has emerged: searchers submit large volumes of speculative transactions, whose profitability is resolved only at execution time. We refer to this as spam MEV. On major rollups, it can at times consume more than half of block gas, even though only a small fraction of probes ultimately results in a trade. Despite growing awareness of this phenomenon, there is no principled framework for understanding how blockchain design parameters shape its prevalence and impact. We develop such a framework, modeling spam transactions competing for on-chain opportunities under a competitive equilibrium that drives their profits to zero, and deriving equilibrium spam volumes as a function of block capacity, minimum gas price, and the transaction fee mechanism. Empirical evidence from Base and Arbitrum supports the model: spam grew sharply as block capacity was scaled up and fell when minimum gas prices were introduced. Our analysis yields three main insights. First, spam is always costly: when block capacity is scarce, it displaces users and drives up gas prices; as block capacity grows, it increasingly consumes execution resources, raising network externality, i.e., the cost of provisioning and processing blocks. We show that spam takes an increasing share of each additional unit of block capacity, so capping it before all users are included creates a favorable trade-off: forgoing a small amount of user welfare eliminates disproportionate spam and externality. Second, we extend the analysis to priority fee ordering and show that ordering transactions by gas price helps reduce spam, as spammers must pay more to reach early block positions. Third, as user demand grows and blockspace is scaled accordingly, spam's share of block capacity plateaus rather than growing indefinitely.
Software engineering courses often require rapid upskilling in supporting knowledge areas such as domain understanding and modeling methods. We report an experience from a two-week milestone in a master's course where 29 students used a customized ChatGPT (GPT-3.5) tutor grounded in a curated course knowledge base to learn cryptocurrency-finance basics and Domain-Driven Design (DDD). We logged all interactions and evaluated a 34.5% random sample of prompt-answer pairs (60/~174) with a five-dimension rubric (accuracy, relevance, pedagogical value, cognitive load, supportiveness), and we collected pre/post self-efficacy. Responses were consistently accurate and relevant in this setting: accuracy averaged 98.9% with no factual errors and only 2/60 minor inaccuracies, and relevance averaged 92.2%. Pedagogical value was high (89.4%) with generally appropriate cognitive load (82.78%), but supportiveness was low (37.78%). Students reported large pre-post self-efficacy gains for genAI-assisted domain learning and DDD application. From these observations we distill seventeen concrete teaching practices spanning prompt/configuration and course/workflow design (e.g., setting expected granularity, constraining verbosity, curating guardrail examples, adding small credit with a simple quality rubric). Within this single-course context, results suggest that genAI-supported learning can complement instruction in domain understanding and modeling tasks, while leaving room to improve tone and follow-up structure.
Adi Wijaya, Budi Hermawan, Wiga Maulana Baihaqi, Catur Supriyanto
This study examines the evolution of Intelligent and Secure Smart Hospital Ecosystems using a Scoping Review with Bibliometric Analysis (ScoRBA) to map research patterns, identify gaps, and derive policy implications. Analyzing 891 journal articles from Scopus (2006-2025) through co-occurrence analysis, network visualization, overlay analysis, and the Enhanced Strategic Diagram (ESD), the study applies the PAGER framework to link Patterns, Advances, Gaps, Research directions, and Evidence-based policy implications. Findings reveal three interrelated clusters: AI-driven intelligent healthcare systems, decentralized privacy-preserving digital health ecosystems, and scalable cloud-edge infrastructures, showing a convergence toward integrated ecosystem architectures where intelligence, trust, and infrastructure reinforce each other. Despite progress in AI, blockchain, and cloud computing, gaps remain in interoperability, real-world implementation, governance, and cross-layer integration. Emerging themes such as explainable AI, federated learning, and privacy mechanisms highlight areas needing further research. Policy-relevant recommendations focus on coordinated governance, scalable infrastructure, and secure data ecosystems, particularly for developing country contexts. The study bridges bibliometric evidence with actionable policies, supporting informed decision-making in smart hospital development.
Assistive technologies increasingly support independence, accessibility, and safety for older adults, people with disabilities, and individuals requiring continuous care. Two major categories are virtual assistive systems and robotic assistive systems operating in physical environments. Although both offer significant benefits, they introduce important security and privacy risks due to their reliance on artificial intelligence, network connectivity, and sensor-based perception. Virtual systems are primarily exposed to threats involving data privacy, unauthorized access, and adversarial voice manipulation. In contrast, robotic systems introduce additional cyber-physical risks such as sensor spoofing, perception manipulation, command injection, and physical safety hazards. In this paper, we present a comparative analysis of security and privacy challenges across these systems. We develop a unified comparative threat-modeling framework that enables structured analysis of attack surfaces, risk profiles, and safety implications across both systems. Moreover, we provide design recommendations for developing secure, privacy-preserving, and trustworthy assistive technologies.
Stephen M. Wilkins, Jack Turner, Connor Sant Fournier, Behnood Bandi · 5 authors
With traditional sources of funding for astronomical research under increasing pressure, it is timely to explore innovative alternative mechanisms. We therefore introduce GalaxyCoin, a novel cryptocurrency whose issuance, validation, and economic evolution are anchored to real astrophysical objects - galaxies. GalaxyCoin links digital scarcity to observational astronomy by using galaxy catalogues to parametrise token generation, distribution, and long-term supply growth, providing a transparent, immutable, and independently verifiable foundation for the currency. We present the conceptual design of GalaxyCoin, highlight its potential advantages over conventional cryptocurrencies, and examine its broader implications for sustainability, trust, and public engagement at the intersection of astronomy, data-driven science, and blockchain technology. A central feature of GalaxyCoin is that it directly incentivises the discovery and spectroscopic confirmation of galaxies, aligning financial reward with the production of high-quality astronomical data. In terms of monetary design, its supply elasticity lies between that of fiat currencies and fixed-supply cryptocurrencies, making it distinctive in both economic structure and scientific purpose.
Purpose: Cyber fraud and money laundering are growing threats to the integrity of operations in the Nigerian banking sector, which undercuts the confidence of customers. This study examined the influence of FinTech solutions specifically smart contracts and cryptographic security on fraud prevention in Nigerian deposit money banks (DMBs), in view of the increasing incidence of cyber fraud and money laundering in the sector. Methodology: The study adopted a quantitative research design, underpinned by the Technology Acceptance Model (TAM), agency theory, and control theory. A cross-sectional survey was conducted on 312 management and IT employees drawn from five selected DMBs in Lagos State. Data collected were analyzed using descriptive statistics and multiple regression analysis. Results and conclusion: The findings revealed that smart contracts have a positive and statistically significant effect on the prevention of cyber fraud (r = 0.408, p < 0.001), while cryptographic security exerts a strong and significant influence on the prevention of money laundering (r = 0.433, p < 0.001). The study concluded that these FinTech solutions are effective tools for enhancing fraud prevention and improving the security architecture of Nigerian banks. Implication of findings: The study implies that deposit money banks should prioritize investment in FinTech innovations, while regulatory authorities should establish supportive frameworks to facilitate their adoption, thereby strengthening financial security and restoring customer confidence in the banking system.
Three model substitution scenarios were executed against a live inference endpoint with real HTTP requests, signed attestation JWTs, and OPA policy enforcement. In each scenario, every tested workload, artifact, or API identity control relevant to that scenario — workload JWT validation, health checks, gateway process continuity, artifact manifest integrity, API key authentication — remained valid while the model changed. In each scenario, a structural identity measurement based on activation geometry during a standard forward pass detected the substitution and the enforcement layer denied the request. Three substitutions were tested and three were detected, with zero false accepts in this run. The warm-path verification latency was 5.7–6.7 seconds on a single A100 with the model already loaded. The complete evidence chain — before/after measurement results, attestation claim summaries, OPA policy evaluations, and HTTP response codes — is published alongside this note as machine-readable JSON. This is a technical note, not a numbered entry in the research series. Supplementary Material. This note is accompanied by three machine-readable evidence files: cat3_results.json (structured results for all three scenarios, including the full before/after evidence chain for Scenario A with signed attestation claims, OPA policy evaluations, and HTTP response codes), manifest_authorized.json (SHA-256 build manifest for the enrolled model, 10 files, all verified), and manifest_substituted.json (SHA-256 build manifest for the substituted model, 10 files, all verified). All three files are available for download as supplementary files attached to this record. The Neural Network Identity Series — Mathematical foundations, empirical validation, and governance frameworks for verifying which model is running Newest addition: Technical Note: The Disappearing Window — AI Logprob Access Withdrawal and the Structural Verifiability of Frontier Model Contracts (DOI: 10.5281/zenodo.20362098) Paper 1: The δ-Gene: Inference-Time Physical Unclonable Functions from Architecture-Invariant Output Geometry (DOI: 10.5281/zenodo.18704275) Paper 2: Template-Based Endpoint Verification via Logprob Order-Statistic Geometry (DOI: 10.5281/zenodo.18776711) Paper 3: The Geometry of Model Theft: Distillation Forensics, Adversarial Erasure, and the Illusion of Spoofing (DOI: 10.5281/zenodo.18818608) Paper 4: Provenance Generalization and Verification Scaling for Neural Network Forensics (DOI: 10.5281/zenodo.18872071) Paper 5: Beneath the Character: The Structural Identity of Neural Networks — Mathematical Evidence for a Non-Narrative Layer of AI Identity (DOI: 10.5281/zenodo.18907292) Paper 6: Which Model Is Running?: Structural Identity as a Prerequisite for Trustworthy Zero-Knowledge Machine Learning (DOI: 10.5281/zenodo.19008116) Paper 7: The Deformation Laws of Neural Identity (DOI: 10.5281/zenodo.19055966) Paper 8: What Counts as Proof? — Admissible Evidence for Neural Network Identity Claims (DOI: 10.5281/zenodo.19058540) Paper 9: Composable Model Identity — Formal Hardening of Structural Attestations in the Enterprise Identity Stack (DOI: 10.5281/zenodo.19099911) Paper 10:Where Identity Comes From: Path Sensitivity and Endpoint Underdetermination in Neural Network Training (DOI: 10.5281/zenodo.19118807) Paper 11: Post-Hoc Disclosure Is Not Runtime Proof: Model Identity at Frontier Scale (DOI: 10.5281/zenodo.19216634) Paper 12: Family-Dependent Response to Reasoning Distillation Across Structural and Functional Identity Layers (DOI: 10.5281/zenodo.19298857) Paper 13: Safety-Alignment Removal as a Model-Identity Failure — Structural Evidence from Published Weight-Level Mutation Checkpoints (DOI: 10.5281/zenodo.19383019) Technical Note: Agent Identity Is Not Model Identity (DOI: 10.5281/zenodo.19240883) Technical Note: Gap Invariance: Why PPP Measurements Are Domain-Independent by Construction (DOI: 10.5281/zenodo.19275524) Technical Note: Measured Model Substitution Under Valid Agent Credentials (DOI: 10.5281/zenodo.19342848) Technical Note: Artifact Identity Is Not Runtime Identity — Trustfall Lite and the Boundary of File-Level Model Verification (DOI: 10.5281/zenodo.20019127) Formal Verification Stack for Neural Network Structural Identity (IT-PUF Coq Proofs) (DOI: 10.5281/zenodo.18930621) Copyright (c) 2026 Anthony Ray Coslett / Fall Risk AI, LLC. All Rights Reserved. Confidential and Proprietary. Patent Pending (Applications 63/982,893, 63/990,487, 63/996,680, 64/003,244).
Giovanni Seraghiti, Kévin Dubrulle, Arnaud Vandaele, Nicolas Gillis
Nonnegative matrix factorization (NMF) approximates a nonnegative matrix, $X$, by the product of two nonnegative factors, $WH$, where $W$ has $r$ columns and $H$ has $r$ rows. In this paper, we consider NMF using the component-wise L1 norm as the error measure (L1-NMF), which is suited for data corrupted by heavy-tailed noise, such as Laplace noise or salt and pepper noise, or in the presence of outliers. Our first contribution is an NP-hardness proof for L1-NMF, even when $r=1$, in contrast to the standard NMF that uses least squares. Our second contribution is to show that L1-NMF strongly enforces sparsity in the factors for sparse input matrices, thereby favoring interpretability. However, if the data is affected by false zeros, too sparse solutions might degrade the model. Our third contribution is a new, more general, L1-NMF model for sparse data, dubbed weighted L1-NMF (wL1-NMF), where the sparsity of the factorization is controlled by adding a penalization parameter to the entries of $WH$ associated with zeros in the data. The fourth contribution is a new coordinate descent (CD) approach for wL1-NMF, denoted as sparse CD (sCD), where each subproblem is solved by a weighted median algorithm. To the best of our knowledge, sCD is the first algorithm for L1-NMF whose complexity scales with the number of nonzero entries in the data, making it efficient in handling large-scale, sparse data. We perform extensive numerical experiments on synthetic and real-world data to show the effectiveness of our new proposed model (wL1-NMF) and algorithm (sCD).
Dilli Prasad Poudel, Thaisa Comelli, Sophie Blackburn, Rojani Manandhar · 5 authors
The decentralization of authority, capability and finance is widely considered to be best practice in urban risk governance. Drawing on the concept of misframing from critical justice theory, we analyse injustices arising from the de jure decentralization of risk governance in Nepal, scrutinizing multi-scalar urban risk governance and its impact on resilient and equitable urban planning. Informed by qualitative research conducted from 2019 to 2024, we ask: How does the (mis)framing of risk governance affect local actors’ capacities to manage risks? And to what extent can inclusive, risk-informed urban planning and policy facilitate just decentralization? We identify a disconnect between risk-management responsibilities assigned to local government and its capacity to meet these expectations. Proposing a typology of misframing, we provide recommendations for the design and deployment of more equitable and contextually appropriate financial, technological and administrative decentralization as a pathway to justice that can overcome rigid scalar jurisdictions.
This study examines the development and intellectual structure of fraud detection research through a bibliometric analysis. Using data extracted from a major scientific database and analyzed with bibliometric visualization tools, the study maps publication trends, influential contributors, and thematic evolution within the field. The findings reveal that fraud detection research is strongly centered on machine learning and increasingly shaped by advances in deep learning, neural networks, and data-driven approaches. At the same time, the field has expanded beyond traditional financial contexts into broader digital ecosystems, including cybersecurity, blockchain, and data privacy. The analysis also highlights a clear shift from conventional statistical methods toward more adaptive and complex models capable of handling large-scale and interconnected data. In addition, emerging themes such as predictive analytics, risk management, and decentralized finance indicate a growing orientation toward real-world application and decision-making. Overall, the study provides a comprehensive overview of the research landscape, identifies key trends and gaps, and offers directions for future research, particularly in integrating technological innovation with practical, ethical, and system-level considerations.
This study explores the integration of blockchain technology with anti-money laundering (AML) systems to enhance transaction transparency, ensure immutable audit trails, and reduce regulatory non-compliance. Through a mixed-methods approach, including a systematic literature review and hypothetical dataset analysis, the research examines blockchain’s potential to address AML challenges in financial institutions. Findings indicate that blockchain-enabled AML systems improve transaction traceability by 35%, reduce compliance costs by 20%, and enhance audit reliability through immutable ledgers. However, scalability and regulatory harmonization remain barriers. The study proposes a framework for blockchain-AML integration and offers policy recommendations for stakeholders. These results contribute to the discourse on leveraging distributed ledger technology for financial regulatory compliance, highlighting practical and theoretical implications for global banking systems.
Adegboyega Afolabi, Modupe M. Adesemowo, Olayemi O. Amosun, M. Olamide Otuyelu · 6 authors
As digital intermediation accelerates, Nigerian deposit money banks (DMBs) confront rising cyber-enabled fraud since the launch of Bitcoin in 2009, despite ongoing reforms. Most blockchain research still centres on cryptocurrencies, with relatively few studies examining their applications in other industries. This study investigates whether blockchain technology (smart contracts, permissioned distributed ledgers, and secure digital wallets) is associated with lower fraud in Nigerian DMBs.Using survey data from 120 bankers across five institutions spanning international, national, and regional licenses, we estimate Ordinary Least Squares (OLS) models relating each BCT dimension, and a composite index, to two outcomes: spread of fraud (SOF) and internet fraud activities (IFA). Reliability analysis shows strong internal consistency (α = 0.75–0.91). Models include robustness checks for multicollinearity and specification. Results indicate that higher perceived deployment of smart contracts, distributed ledger, and digital wallet capabilities is negatively and significantly associated with SOF and IFA; a composite BCT index positively predicts overall fraud-reduction assessments. These findings align with recent sectoral evidence that blockchain adoption lowers fraud-related costs and enhances transaction integrity in banking. Given Nigeria’s elevated incidence of electronic fraud in retail payments, the practical implication is that embedding programmable controls, tamper-evident shared records, and cryptographic authentication can harden high-risk processes. We recommend that regulators and DMBs advance permissioned BCT pilots integrated with Anti-Money Laundering (AML) and Know Your Customer (KYC) workflows, strengthen reporting standards, and build human-capital readiness. Beyond cryptocurrency, enterprise-grade BCT offers credible pathways to reduce fraud externalities and improve operational resilience in Nigeria’s banking sector. Keywords: Blockchain; Smart contracts; Distributed ledger; Digital wallet; Bank fraud; Nigeria.
This record contains the research monograph Hyper–Omniverse Unified Quantum Field Theory: A Hidden Ambient Geometric Multiverse for Single-Parameter UV–Finite Particle Physics and Vacuum–Creation Cosmology by Giovanni Joseph Chiappone. The volume presents Hyper–Omniverse Unified Quantum Field Theory (HOUQFT) as a sector–plane–resolved quantum field theory formulated on an ambient multi–geometric–time manifold and read on effective four-dimensional slices through geometric–time locking (GTL). Its central structural rule is that hyper–propagator kernels dress only uncut internal lines, while external legs and physical unitarity-cut lines remain undressed. In this way, the framework modifies internal quantum transport while preserving the observable scattering sector. The monograph is organized as a verification-first research volume rather than as a conventional linear exposition. It is designed to be locally auditable: core claims are paired with explicit assumptions, a front-loaded verification map, and a bounded proof architecture. The proof-critical overlap core is concentrated in Part II, where the monograph develops the BRST / Slavnov–Taylor structure and all-orders ultraviolet-finiteness results under the stated kernel hypotheses. Parts I, III, and IV provide the geometric foundations, the kinematic and LSZ framework, and the vacuum-creation cosmology / phenomenology program that place those core results within the broader HOUQFT and O-QFT structure. At the formal level, the monograph develops an ambient-first, lock-later construction. The theory is first posed on a multi–geometric–time manifold, with sector–plane labels, plane-wise ordering, and the relevant operator structure fixed explicitly before any reduction to observable physics is taken; only afterward are observables read on the locked effective 1+3 slice. Within that setting, the monograph advances two paper-grade core claims in directly auditable form: exact plane-wise non-Abelian BRST / Slavnov–Taylor control without counterterm vertices, and graph-by-graph Euclidean ultraviolet finiteness to all loop orders at fixed damping scale. On that foundation, the framework is extended toward a broader phenomenological program including vacuum-creation cosmology, late-time H0 interpretation, CMB phenomenology, and a controlled low-l anisotropic extension tied to large-angle directional structure. This record is intended to serve as the book-length version of record for the framework. It consolidates material previously distributed across multiple working preprints into a single notation system, a single dependency graph, and a single citable monograph. It is meant to be read alongside the companion reproducibility and audit records listed below, which preserve the principal numerical support objects referenced in the cosmology and acoustic-analysis portions of the work. Companion records Full Pantheon+ late-time cosmology reproducibility pack: DOI 10.5281/zenodo.19362753 Acoustic analysis reproducibility pack: DOI 10.5281/zenodo.19339204 Retained Hubble-tension audit snapshot: DOI 10.5281/zenodo.19339206 Notes This monograph is a research monograph and technical reference, not a general-audience introduction. The associated reproducibility packs should be cited separately when referring to the numerical pipelines, retained-run audit materials, or acoustic-analysis support objects they archive. Related works Structural Internal–Line Damping from Geometric–Time Locking: BRST–Exact Sector–Plane Quantization of Yang–Mills with Exact Slavnov–Taylor Identities and All–Orders UV Finiteness (DOI 10.5281/zenodo.19361731): the formal companion article for the monograph's proof-critical overlap core. It presents the BRST / Slavnov–Taylor and all-orders ultraviolet-finiteness results in paper form, while the present monograph provides the expanded verification-first architecture, intermediate derivations, technical appendices, assumption ledgers, and broader geometric and phenomenological context that underpin those claims. From Hyper–Propagators to Selective Damping: A Sector–Plane–Resolved Stability Framework for Fusion, Plasma Control, Beam Transport, and Wave Technologies (DOI 10.5281/zenodo.19361740): a downstream framework-and-applications article that develops the selective-damping and stability-control consequences of the hyper–propagator / GTL mechanism across fusion, plasma, beam, wave, and related technological settings. Relative to the monograph, this paper pushes outward from the formal core toward a generalized application framework. Omniverse QED Geo–Phase Damping in the Hydrodynamic Window: A First–Principles Route to Rayleigh–Taylor Suppression for MagLIF (DOI 10.5281/zenodo.18948867): a focused application article deriving the Omniverse-QED geo-phase damping mechanism in the ignition-relevant hydrodynamic regime and applying it to Rayleigh–Taylor suppression in MagLIF. Within the broader research program, it serves as the prototype derived application case that later feeds into the wider selective-damping framework. These records are not alternate versions of the present monograph. They are distinct but connected publications within the same research program: one formal companion article that overlaps the monograph’s theorem-level core, and two downstream application papers that develop specific physical and technological consequences of the framework.
Cross-domain data exchange is an important technical approach for realizing the value of data assets. However, lacking a single trusted root CA across domains, cross-domain schemes often encounter difficulties in authentication, controlled data flow, and fine-grained authorization. We propose a cross-domain data sharing scheme that uses decentralized identifiers and threshold proxy re-encryption. This scheme adopts the intra-domain leader node to verify the user identity, and the inter-domain multi-agent nodes collaborate in a threshold manner to handle cross-domain registration requests and re-encryption requests. Through threshold cooperation, the problem of single point of failure is effectively solved. The hash value of cross-domain registration information is stored on the blockchain, leveraging the immutable and traceable characteristics of blockchain to achieve trusted cross-domain data sharing. In addition, we introduce a ciphertext version tag to enable fast updates of re-encryption keys and use zero-knowledge proofs to verify re-encrypted ciphertext correctness. The security analysis indicates that our scheme has IND-CCA2 security under the DBDH assumption and can effectively resist collusion attacks. Performance analysis shows that our scheme is efficient, and can better meet the needs of cross-domain data sharing.
This analysis examines the role of crypto-assets, particularly Bitcoin, in an investment portfolio. The crypto-asset market, with its rather rapid growth, has begun to attract the interest of a broad range of investors, and despite the uncertainties still existing in the legal framework regulating the sector, international experience shows that the involvement of institutional structures is also growing. The study investigates the impact of including Bitcoin – the largest crypto-asset – within a portfolio of traditional investment assets, focusing on the dynamics of portfolio risk-return indicators to reveal the investment potential of cryptocurrencies. Correlations with other assets were considered, and the possibility of constructing a Markovitz portfolio by including cryptocurrency in a traditional portfolio was considered. Within the framework of portfolio analysis, three scenarios were discussed to see the impact of cryptocurrency inclusion on the portfolio's risk-return indicators, Sharpe ratio. The results of the study generally confirm the hypothesis that cryptocurrencies can serve as a tool to enhance portfolio performance when included in a limited proportion.