Background Cross-border credit recognition in Sino-Foreign Cooperative Education (SFCE) suffers from data fragmentation, regulatory conflicts (e.g., GDPR vs. China’s Data Security Law), and low efficiency. Objective This paper proposes ZkHybridChain, a dual-layer blockchain credit bank (BCB) framework to resolve the privacy-compliance-efficiency trilemma. Methods The hybrid architecture integrates Polygon zkEVM (public credential hashing) and Hyperledger Fabric (private raw data storage). Zero-Knowledge Proofs (ZKP) and three-tiered smart contracts enable automated credit conversion (ECTS↔CNQF) and privacy-preserving verification. Results Experiments on 10,000 SFCE records show 58% efficiency gain (full lifecycle from ∼1,200 s to <9 s), cross-border latency <9 s, throughput up to 1,620 TPS, and ZKP verification latency 135 ms (93.7% success rate). Conclusion ZkHybridChain provides a scalable, GDPR/DSL-compliant solution for global education trust networks. Future work includes post-quantum cryptography and lightweight client protocols.
The realms of metaverse and finance have been completely revolutionized through the application of blockchain technology. This technology offers convenience, transparency, security, and decentralization to the virtual world while overcoming the inefficiencies of the traditional financial landscape. The present chapter highlights the various services offered by blockchain technology in the metaverse, such as security, interoperability, and ownership status, especially in the area of finance. A digital landscape with a large number of users sharing information from various geographical locations using an internet connection is called the metaverse. Blockchain technology ensures transparency and security in the metaverse by building trust among users. The users get complete authority over their digital assets, thereby enhancing their participation in the digital realm. In the financial sector, the traditional financial system is transformed through the introduction of blockchain technology, such as cryptocurrencies like Bitcoin and Ethereum, decentralized finance (DeFi), smart contracts, and asset tokenization. Cryptocurrencies, like Bitcoin 506 and Ethereum, provided by blockchain technology, are digital currencies that ensure secure transactions and do not need any authority to act as a middleman. Decentralized finance (DeFi), based on decentralization, facilitates peer-to-peer financial transactions. Smart contracts are automatically executed agreements or contracts made using blockchain technology, which makes the process of transactions easier. Asset tokenization is a representation of the value of assets as digital tokens. However, blockchain technology also presents challenges in various services, necessitating the need to address them to improve opportunities.
The growing popularity of cryptocurrencies across the globe has generated concerns. The phenomenon has challenged existing financial regulatory frameworks prompting countries to consider partial or absolute recognition of the medium as tradable securities, for exchange or settlement of accounts, after the manner of fiat currency, but parallel to it. Fundamentally, the aim of this paper is to ascertain whether cryptocurrencies may lawfully be used, and to what extent in Nigeria. The study engages the doctrinal (conceptual) methodology for legal research which is basically library based, leveraging primary and secondary source materials for the rigorous analysis. With particular focus on the Investment and Securities Act 2025 the paper makes a structured analysis and review of relevant regulations on securities and currencies in Nigeria to determine: i). whether all manifestations of cryptocurrencies were within the contemplation of statute, and ii). the effect of the new law on the legality or otherwise of virtual assets in Nigeria. The result reveals at first, that the debate on legal assessment of cryptocurrencies persists and issues are still not fully resolved; second, the status and nature of digital currency presents it as a specie of electronic promissory note capable of creating legal obligations and values enforceable by judicial process if properly harnessed. In concluding, the paper asserts that cryptocurrency could be traded on the stock market and licensed bureau de change platforms like other foreign currencies with the right statutory atmosphere and such trades would enrich Nigeria’s tax economy as it is the case with Canada.
Munir Ahmad, Md Zahidul Islam, M. S. Raña, Saddam Hossain
This chapter examines the role of blockchain technology in strengthening risk mitigation within sustainable finance ecosystems. As sustainable finance seeks to align investments with ESG goals, it faces challenges like greenwashing, inconsistent data, carbon credit fraud, and complex regulatory landscapes. Blockchain offers a transparent, decentralized, and tamper-proof infrastructure to address these vulnerabilities. Through smart contracts, automated compliance, and real-time verification, blockchain enhances trust, accountability, and efficiency in ESG practices. The chapter explores use cases and frameworks to demonstrate blockchain's potential to build resilient and credible, and sustainable finance systems.
As autonomous driving technology advances towards Level 4 and 5, virtual simulation has become an indispensable tool for safety validation. However, a critical ''trust gap'' exists between developers and regulators; submitting raw simulation logs poses risks of data tampering (integrity issues) and intellectual property leakage (privacy issues). To address this, we propose ZK-V, a universal, privacy-preserving verification framework designed to interface with various autonomous driving simulators. By leveraging Zero-Knowledge Proofs and blockchain technology, ZK-V allows a Prover to cryptographically demonstrate that a simulation run adhered to specific safety constraints such as collision avoidance and speed limits without revealing the underlying telemetry data. This paper outlines the simulation-agnostic system architecture and constraint logic, offering a scalable solution for decentralized, trust-free certification in the Web 4.0 mobility era.
Maximal Extractable Value (MEV) in decentralized finance (DeFi) enables searchers to profit from transaction ordering and arbitrage opportunities across Automated Market Makers (AMMs). Among MEV strategies, atomic triangular arbitrage is widely deployed due to its deterministic execution within a single transaction. However, executing profitable arbitrage under realistic constraints, such as limited wallet balance, pool liquidity, gas costs, and blockchain latency, remains a challenging optimization problem. In this work, we formulate atomic triangular arbitrage as a constrained optimization problem that jointly selects an ordered three-pool path and trade amount to maximize net profit. To solve this non-convex problem, we propose a Deep Reinforcement Learning approach based on Proximal Policy Optimization (PPO). Experimental results show that while exhaustive grid search attains the highest returns, it requires a significantly high amount of inference time, making it infeasible for on-chain execution. In contrast, the proposed PPO agent achieves millisecond-level inference latency while generating consistent positive profit. These findings highlight a fundamental speed–profit trade-off in MEV extraction and demonstrate that PPO provides an effective and practical solution for atomic triangular arbitrage in DeFi.
Abstract - Traditional machine learning-based fraud detection frameworks treat transaction registries as static, isolated, non-relational entities. While effective for simple localized pattern recognition, these methods are structurally blind to multi-hop relational dependencies, automated asset splitting, or continuous temporal dynamics characteristic of modern financial fraud within decentralized finance (DeFi) networks. This paper presents a complete structural paradigm utilizing Temporal Graph Neural Networks (TGNNs) to identify non-linear anomaly patterns directly in transaction graphs. By projecting raw financial data streams as dynamic, continuous-time directed graphs, our model learns evolving node and edge representations without relying on synthetic tabular oversampling mechanisms. Empirical simulation methodologies demonstrate that shifting the analytical paradigm from local, isolated classification to global temporal network topology minimizes false positives by 34.2% while significantly improving minority-class recall. Key Words: Credit Card Fraud, Graph Neural Networks, Temporal Embeddings, Class Imbalance, Deep Learning, Decentralized Finance (DeFi)
Nick Riccardi, Rodney Paul, Andrew Weinbach, Hamid Ekbia
This study examines behavioral pricing patterns in blockchain-based fantasy sports markets by analyzing non-fungible token (NFT) sales on Sorare.com, a decentralized platform where users buy, sell, and compete with digital player cards. Each NFT corresponds to a licensed professional soccer player and is traded in a secondary market on Ethereum-based infrastructure. We construct a unique dataset by linking player performance data with transaction-level NFT sales across multiple seasons, focusing on the Rare and Super Rare card tiers. To isolate the effects of recent performance on secondary market prices, we develop a matching algorithm that connects NFT transaction records to individual card IDs based on sale timestamps and card-specific metadata. This structure allows us to test whether player NFTs are priced efficiently, or whether recent on-field success leads to temporary price inflation consistent with hot hand bias. Our results align with the presence of performance-chasing or hot hand pricing, where recent form leads to a temporary inflation of perceived value. Our framework builds on prior work examining the hot hand hypothesis in traditional sports betting markets—including studies by Camerer (1989), Brown and Sauer (1993), and Paul and Weinbach (2005, 2011, 2014)—and extends this behavioral lens to tokenized digital assets.
This paper estimates the carry embedded in listed IBIT options and compares it with the carry embedded in matched CME bitcoin futures. Put-call parity recovers an implied forward on the ETF; BlackRock's daily holdings file maps each ETF share into bitcoin units; and CME futures prices and BRRNY, a U.S. close bitcoin reference rate, provide the corresponding futures-market carry. The difference in carry implied by these two products is consistent with frictions that limit cross-margining between spot bitcoin or ETF exposure and CME futures. In the selected-strike IBIT sample of 386 date-bucket observations, the mean wedge is 2.58 percent and the median wedge is 2.52 percent, both measured in annual percentage points. The result is consistent with segmented collateral and margin systems limiting arbitrage between regulated bitcoin-exposure venues.
The Manufacturer Usage Description (MUD) standard enables enforcement of network restrictions for IoT devices based on their expected network traffic, as specified by manufacturers in an online MUD file. Devices advertise a URL pointing to this file, yet the standard does not define how to securely bind the issuing device to its profile. As a result, malicious devices can manipulate network policy enforcement by advertising valid URLs referencing genuine MUD profiles, but not intended for that device. Although MUD defines a certificate-based secure issuance method, current deployments rely on the insecure DHCP-based extension due to simpler integration. Existing solutions either depend on Public Key Infrastructure (PKI), break standard compliance, require excessive active manufacturer involvement, or overlook secure profile updates. In this paper, we present FIDEM, a standard-compliant framework for securing DHCP-based MUD URL issuance. FIDEM provides cryptographic binding between IoT devices and their MUD profiles by leveraging Zero-Knowledge-Proof authentication, eliminating PKI reliance, minimizing manufacturers' involvement, and supporting secure profile updates. Formal analysis shows that FIDEM withstands stronger adversaries than in prior work, including supply-chain compromise and attacks using legitimate devices as cryptographic oracles. Our real-world evaluation on two reference constrained devices (ESP32-S3 and ESP32-C6) demonstrates minimal overhead compared to standard DHCP (approximately 5ms and 20mJ) and significant improvements over certificate-based benchmarks (approximately x20 faster, and 35% less energy).
Shiho Kim, Ho Suk, Roberto Di Pietro, Davor Svetinović · 7 authors
ZABAPAD (Zero-knowledge proof And Blockchain for WEB 4.0: Advancing the Post-quantum And Decentralized Era) is a workshop focusing on zero-knowledge technologies, blockchain infrastructure, and post-quantum readiness for the emerging Web 4.0 ecosystem. This workshop emphasizes real-world deployments, empirical measurements, and interoperability across Web and non-Web domains. In particular, ZABAPAD explores the convergence of AIoT and ZKP—redefining identity and trust models beyond SIM in mobile networks, IP in Web 2.0, and NFT in Web 3.0. As AIoT systems evolve toward decentralized, post-quantum infrastructures, ZKPbased authentication and AIoT SIM functionalities are emerging as key enablers of secure, privacy-preserving, and verifiable connectivity among intelligent devices, vehicles, and edge services. This theme extends to ZKML, Layer-2 proving/verification, TEE+ZK integration for verifiable compute, and post-quantum migration of identities, wallets, ledgers, and protocols. Expected outcomes include: (1) a practitioner-oriented adoption playbook, (2) an interoperability and standards checklist, (3) a curated set of reproducible benchmarks and datasets, and (4) a catalog of failure modes and mitigations for domains such as finance, mobility, healthcare, AIoT, public services, supply chain, and AI/ML. ZABAPAD complements the Web Conference and Web 4.0 communities by uniting global researchers and developers to chart actionable, trustworthy pathways toward the post-quantum, decentralized, and intelligent Internet.
Chapter 9 of the Vital Intelligence Doctrine (VID) introduces Tensegrity Architecture as a paradigm shift for organizational design. Moving away from rigid hierarchical 'pyramids,' this chapter proposes a model based on 'Discontinuous Compression and Continuous Tension.' It explores how to build self-regulating organizations using Synergetics, autonomous VID-units, and dynamic messaging matrices. By implementing these principles, leaders can create resilient, antifragile entities that operate through internal balance rather than central control. Keywords: Vital Intelligence Doctrine, VID, Tensegrity, Synergetics, Decentralized Governance, Organizational Architecture, Systemic Resilience, Self-organizing Organizations.
The proliferation of centralized carrier-based authentication systems has exposed critical vulnerabilities in the preservation of privacy and personal data protection. Current implementations in Korea, such as PASS and KakaoTalk identity services, rely on centralized architectures that create single points of failure and require excessive disclosure of personal information. The large-scale security breach of SK Telecom's USIM infrastructure in 2025, affecting 23 million subscribers, highlights the urgent need for a paradigm shift in identity authentication.?This paper proposes a decentralized identity authentication system leveraging W3C Decentralized Identifiers (DIDs) and Verifiable Credentials (VCs), combined with Zero-Knowledge Proofs (ZKPs). Our framework integrates Schnorr signatures with Sigma-protocol-based ZKPs to enable privacy-preserving authentication without revealing private keys. A three-layer architecture—comprising cryptographic, identity, and credential layers—ensures strong cryptographic guarantees based on the discrete logarithm problem over the secp256k1 curve, while eliminating reliance on centralized infrastructure. Performance evaluation shows that signature generation occurs in under 10 ms and verification in under 15 ms, meeting real-time authentication requirements while delivering formal privacy guarantees that are absent in conventional systems.
As quantum computing moves to a cloud-based service model, a privacy–utility dilemma arises: effective Quantum Error Mitigation (QEM) requires circuit visibility, yet circuits and noise models are often proprietary. We propose Blind-QEM, a privacy-preserving framework that enables outsourced mitigation without revealing circuit topology. Using Zero-Knowledge Proofs (ZKPs) and a receipt-based binding mechanism anchored by QPU-signed execution logs, Blind-QEM verifies policy compliance and cryptographically links results to committed circuits. This allows Service Providers to perform global incoherent noise cancellation and readout mitigation using only verified aggregate statistics, ensuring mutual protection of user IP and SP models.
Zero-knowledge proofs (ZKPs) play a critical role in mitigating modern digital threats by enabling verification without disclosure, a key requirement for secure computation in adversarial environments. Among existing constructions, zk-SNARKs and zk-STARKs represent two dominant paradigms with contrasting security, trust, and performance characteristics. While their theoretical foundations are well studied, practical performance under real-world conditions remains less understood. In this work, we present a systematic, implementation-level comparison of zk-SNARKs (Groth16) and zk-STARKs using publicly available reference implementations on a consumer-grade ARM platform. Our empirical evaluation covers proof generation time, verification latency, proof size, and CPU profiling. Results show that zk-SNARKs generate proofs 68x faster with 123x smaller proof size, but verify slower and require trusted setup, whereas zk-STARKs, despite larger proofs and slower generation, verify faster and remain transparent and post-quantum secure. Profiling further identifies distinct computational bottlenecks across the two systems, underscoring how execution models and implementation details significantly affect real-world performance. These findings provide actionable insights for developers, protocol designers, and researchers in selecting and optimizing proof systems for applications such as privacy-preserving transactions, verifiable computation, and scalable rollups.
Certain game-theoretic models of blockchains are discussed in this chapter. These models provide a critical insight into the workings of the blockchain technology. A simple Bitcoin mining contest is described in the next section. This is followed by a Proof-of-Work mining game. A Bitcoin mining game with pooling is next described. An Algorand-like scheme is also examined. Finally a game-theoretic model of the Proof-of-Stake consensus protocol is analyzed. Interpretations and implications of these games are also outlined in their respective sections.
This paper outlines the architecture and methodological foundations of the BeTrueCore modular system, built upon the "Web3 Intuitive Symmetry Methodology" v1.2. Aaddress the critical challenges of destructive sociotechnical pressure, preference falsification, and enforced informational atomization inherent in modern centralized digital ecosystems. This paper is dedicated to the operationalization and mathematical description of the BeTrueCore modular system’s dynamic engine. The article bridges the traditional "verification gap" between abstract ethical-philosophical concepts and their rigorous software implementation. It deploys the concept of a fractal "Build → Measure → Learn" feedback loop, where participants' individual intuitive impulses (the Pulse) are converted into semantic vectors and weighted by the AI-Metronome. Particular attention is paid to the stochastic transition mechanism—the "White Feather Jump"—modeled via the Wiener differential equation as a method for extricating the collective intelligence from algorithmic deadlocks. The study thoroughly examines 9 key sociotechnical risks (including the Dunning-Kruger, Timur Kuran, and Paulo Freire phenomena) and provides systemic responses from the platform modules, secured by ZK-cryptography and Lit Protocol. The paper verifies BeTrueCore as a resilient tool for measuring and Bayesian updating of collective consensus under conditions of inherent systemic noise. The architecture executes a dialectical inversion: transforming isolation from an instrument of suppression into a protective 'digital citadel,' restoring the user’s absolute autonomy over their time and choices under the principle: 'My identity is my castle.' The study formalizes the 'Centaur' hybrid decision-making model. The study formalizes the "Centaur" hybrid decision-making model, where the synergy between non-linear human intuitive potential (Pulse) and AI computational efficiency (Metronom) is mathematically defined through a utility maximization function that accounts for systemic risks and machine ethics. Rather than suppressing the chaotic incoming entropy of the human factor, the algorithmic core converts it into stochastic resonance, enabling the system to escape local minima and converge on global maxima of truth.
The agentic web, where billions of autonomous AI agents discover, communicate, and coordinate across organizational boundaries, requires new foundations spanning technical infrastructure, economic mechanisms, and societal coordination. Just as DNS and HTTP shaped the traditional web's evolution, the architectural decisions we make today for agent registries, protocols, and reputation systems will determine what forms of distributed intelligence emerge tomorrow. This lecture-style tutorial provides a comprehensive framework for understanding this network of AI Agents in a Decentralized Architecture (NANDA), across three development phases: Foundations (discovery, identity, protocols), Agentic Economy (pricing, reputation, markets), and Agentic Society (population dynamics, governance, coordination). Drawing on recent advances in registry architectures, protocol standards, and resolution mechanisms, this tutorial equips participants with conceptual frameworks and practical insights for designing infrastructure that enables safe, scalable, and sustainable agent ecosystems. The tutorial emphasizes forward-thinking perspectives on open challenges and research opportunities while building on web-native standards.
Digital technology has reshaped the concept of ownership in the digital realm. This study explores non-fungible tokens (NFTs) as innovative offerings from heritage sites, focusing on how psychological ownership of these digital assets influences tourists’ real-world behaviors. Four scenario-based experiments across different cultural heritage contexts demonstrate that psychological ownership of tourism NFTs (high-level vs. low-level) influences tourists’ visit intention and stewardship behavioral intentions. The mechanism involves the transfer of psychological ownership from tourism NFTs (the proximal target) to the original cultural heritage (the distal target), which subsequently leads to increased cultural heritage attachment. Furthermore, these effects are attenuated for individuals with a low construal level. These findings advance current knowledge on psychological ownership and NFT implementations in heritage tourism while providing practical guidance for heritage organizations to leverage NFTs.
Customer Service Quality and Loyalty
Diverse Aspects of Tourism Research
Consumer Behavior in Brand Consumption and Identification
The Internet is undergoing constant transformation, driven by emerging paradigms such as Web3 and Artificial Intelligence. Despite these developments, the secure operation of Internet services remains a fundamental prerequisite for ensuring confidentiality, integrity, and availability.
Tangle is a relatively recent distributed ledger technology (DLT), which is specially designed for IoT (Internet of Things) applications. The blockchain technology which is used for the Bitcoin cryptocurrency, relies upon the concept of rewarding the mining node whose newly created block is appended to the chain of blocks. This concept is not feasible in the realm of IoT technology. This is true because: If the Bitcoin blockchain technology is used, then the required transaction fees may turn out to be higher than the value of the IoT transaction itself. IoT networks require higher transaction processing rate than cryptocurrencies. Recall from the chapter on blockchain-throughput of this Volume (Volume 2: Engineering Principles), that the blockchains which support Bitcoin-like applications have a very low transaction processing rate. Further, nodes in the IoT network may or may not have high computational power.