Memory-enabled large language model (LLM) agents, particularly those deployed in long-horizon, tool-using settings such as Web3-style autonomous workflows, introduce security risks that extend beyond single-prompt injection. By persisting and reusing information across interaction steps and sessions, these agents enable memory poisoning attacks in which adversarial inputs modify persistent agent state and influence future decisions after benign intermediate interactions. Recent work on context manipulation and “fake memories” demonstrates that adversarial content can be injected into an agent’s prompt-visible inputs or persistent memory; however, existing evaluations largely analyze such attacks at isolated interaction steps or static context snapshots, obscuring their temporal dynamics. In this paper, we present the first large-scale, trajectory-level measurement framework for analyzing temporal memory poisoning in memory-enabled LLM agents. We construct a schema-constrained dataset of 2,614 multi-step attack trajectories spanning four attack families,chain poisoning, policy rewriting, backdoor triggering, andslow drift, executed over shared persistent memory. We define temporal risk metrics over multi-step interaction trajectories that capture delayed activation, non-monotonic escalation, and the earliest point at which attacks become distinguishable from benign behavior. Our empirical results show that a substantial fraction of attacks remain indistinguishable from benign behavior until late-stage activation, despite exhibiting low or medium risk at all earlier steps. Slow-drift and backdoor-trigger attacks, in particular, systematically evade step-local evaluation until terminal interactions, while chain poisoning and policy rewriting exhibit non-monotonic risk trajectories. These findings demonstrate that memory poisoning risk is inherently temporal and cannot be reliably assessed using prompt-level or step-isolated evaluation, motivating trajectory-aware benchmarks for agent security.
This article examines the limitations of existing hybrid rollup solutions and presents an adaptive L2 architecture model that leverages artificial intelligence mechanisms. It is shown that current approaches to combining optimistic and ZK verification are largely based on static rules or manual mode selection, which prevents them from effectively accounting for load dynamics, risk profiles, and domain-specific properties of applications. Based on an analysis of optimistic, ZK, and hybrid rollups, an adaptive hybrid rollup model with AI-based transaction routing is proposed. This model combines transaction classification, GNN-based decision making, LSTM-based network condition forecasting, a dual-path execution system, and a continuous learning module. The article describes a Predictive Routing Algorithm that performs proactive selection between ZK and optimistic paths, taking into account cost, latency, security, and risk profile, as well as a Dynamic Resources Allocation mechanism that dynamically redistributes resources between the paths. The proposed multi-criteria optimization framework demonstrates the ability to tune objective weights to the specifics of different classes of DeFi and Web3 protocols. It is shown that the implementation of such a model is promising for systems with high transactional intensity, as it enables a shift from manual configurations to automated, data-driven policies for resource and risk management in hybrid rollup architectures.
In decentralized digital economics era, consumer engagement has transitioned from platform-based loyalty to tokenized participation and co-creation. In Web2 brand communities, gamification often produce short-term loyalty due its reliance on external, platform regulated incentives (Deterding et al., 2011). The development of Web3 technologies has integrated verified ownership, tokenized incentives and decentralized governance, providing fresh pathways for sustained consumer engagement (Tapscott & Tapscott, 2016). This study introduces the Tokenized Co-Creation (TCC) Framework, which combines Self-Determination Theory (SDT) (Ryan & Deci, 2000) and Service-Dominant logic Theory (SDL) (Vargo & Lusch, 2004) to explain how Web3 powered gamification mechanics (NFTs, Token utilities and DAOs), satisfy intrinsic motivational needs and drive brand value co-creation (Hollebeek et al., 2019). This study contributes to the emerging literature of technological possibilities and human motivation under a overarching Tokenized Co-Creation(TCC) Framework, thus providing both theoretical advancement and managerial direction for developing a trust-based, participatory brand communities in decentralized setting.
Qian'ang Mao, Jiaxin Wang, Liu Ya, Li Zhu · 6 authors
The decentralized architecture of Web3 technologies creates fundamental challenges for Anti-Money Laundering and Counter-Financing of Terrorism compliance. Traditional regulatory technology solutions designed for centralized financial systems prove inadequate for blockchain's transparent yet pseudonymous networks. This systematization examines how blockchain-native RegTech solutions leverage distributed ledger properties to enable novel compliance capabilities. We develop three taxonomies organizing the Web3 RegTech domain: a regulatory paradigm evolution framework across ten dimensions, a compliance protocol taxonomy encompassing five verification layers, and a RegTech lifecycle framework spanning preventive, real-time, and investigative phases. Through analysis of 41 operational commercial platforms and 28 academic prototypes selected from systematic literature review (2015-2025), we demonstrate that Web3 RegTech enables transaction graph analysis, real-time risk assessment, cross-chain analytics, and privacy-preserving verification approaches that are difficult to achieve or less commonly deployed in traditional centralized systems. Our analysis reveals critical gaps between academic innovation and industry deployment, alongside persistent challenges in cross-chain tracking, DeFi interaction analysis, privacy protocol monitoring, and scalability. We synthesize architectural best practices and identify research directions addressing these gaps while respecting Web3's core principles of decentralization, transparency, and user sovereignty.
Alsaadah Saif Mohammed ALabri, Shahd Ibrahim Ali AL Balushi
Blockchain is a distributed database used to store an unchangeable, permanent record of all transactions. It is operated by processors that are a member of a peer-to-peer (P2P) network and functions as a decentralized database. Demand for decentralized applications (DApps), which provide accountability, safety, and independence beyond conventional centralized systems, is rising as a result of the quick development of blockchain technology. However, combining frontend, back end, and blockchain components into a unified and effective framework might be difficult for DApp designers. In order to simplify the creation of decentralized applications, this study suggests a full-stack blockchain framework that connects various levels. The framework creates an end-to-end development environment designed for compatibility and scalability by utilizing contemporary technologies, such as Solidity, with Web3.js for smart contract integration, React.js for the front-end, and Node.js/Express.js for the backend. Using cryptographic methods and decentralized storage (like IPFS), a layered architecture is intended to provide modularity, effective data flow, and increased security. The suggested framework streamlines DApp development processes, lowers latency in blockchain interactions, and boosts developer efficiency, according to implementation data. By offering a thorough architectural blueprint and execution method for full-stack DApp creation, this study advances the area of blockchain engineering and opens the door for safe, effective, and user-focused decentralized ecosystems.
Decentralized Autonomous Organizations (DAOs) face inherent institutional conflicts between their decentralized governance structures, tokenized incentive mechanisms, and rigid global regulatory frameworks—with the U.S. regulatory landscape (SEC, OFAC, FinCEN) emerging as the most stringent and impactful. In 2024, 7 U.S.-based DAOs were subject to SEC investigations (aggregate penalties of $12.8 million), 18% incurred FinCEN sanctions for OFAC-sanctioned address interactions, and 68% of Base chain DAOs were denied institutional capital due to inadequate compliance documentation. Grounded in institutional economics (regulatory adaptation theory), RegTech principles, and blockchain traceability, this study proposes a “three-dimensional compliance adaptation framework” for DAO governance—integrating a regulatory rule engine (quantitative alignment with U.S. rules), automated on-chain audit report generation (transparency assurance), and dynamic governance optimization (securities risk mitigation). Drawing on the development of the “DAO Shield Pro” system and empirical testing across 7 representative U.S. Base chain DAOs (3 AI-focused, 2 meme-based, 2 investment-focused) over a 6-month period (March–August 2025), the framework achieves: (1) a 67.9% reduction in average compliance risk scores (from 3.8 to 0.98), (2) a 45.6-percentage-point increase in U.S. institutional investor participation (from 7.8% to 53.4%), (3) a 100% SEC regulatory inquiry acceptance rate, and (4) a 64.2% reduction in monthly compliance labor costs (from $19,200 to $6,870). This research fills critical gaps in DAO compliance scholarship by providing a theoretically rigorous, technically actionable, and empirically validated solution tailored to U.S. regulatory requirements (SEC Howey Test, OFAC sanctions screening, PCAOB auditing standards). It advances the field by quantifying ambiguous regulatory rules into executable on-chain logic and delivers a replicable paradigm for global DAO regulatory adaptation—strengthening U.S. competitiveness in the Web3 ecosystem and unlocking an estimated $42–$58 billion in latent institutional investment.
Rob J. Lewis, Jonas Lembrechts, P. D. Walker, Chunli Li · 5 authors
Background and Rationale Despite decades of progress in ecological monitoring, primary biodiversity and environmental data remain unevenly mobilised and poorly interoperable (Hampton et al. 2015, Poisot et al. 2019). Datasets, often gathered with public funds, frequently remain inaccessible or insufficiently described, limiting their reuse in global syntheses (Culina et al. 2018). Ecologists’ concerns about trust, transparency, and control of shared data persist, particularly where data production is resource-intensive or socially embedded. These concerns echo the foundational properties of distributed ledgers, where ownership and governance are distributed across peer networks rather than centralized repositories (Lewis et al. 2023). Forests exemplify both the potential and the challenge of such decentralised infrastructures. As globally significant carbon and biodiversity reservoirs, forests are also deeply fragmented across ownership and jurisdictional boundaries. In Europe alone, over half of forested land is privately owned, yet these actors often lack mechanisms to derive tangible value from stewardship. At the same time, digital twins (macroecological models) that integrate in situ and remotely sensed data, are becoming central to forest policy and monitoring frameworks (e.g., Food and Agriculture Organization of the United Nations (FAO), Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services (IPBES), Global Biodiversity Framework (GBF)). ForestWeb3 (FW3) hypothesizes that a decentralised, Findable Accessible, Interoperable, Reusable (FAIR; Wilkinson et al. 2016, Nosek et al. 2022)-aligned data network can unlock the latent value of underused biodiversity data while building trust and incentives for participation.. Objectives Mobilisation and harmonisation of forest biodiversity and environmental data (Objective 1): to spearhead a shift from data curation to data stewardship through a decentralised data infrastructure built on open-source blockchain frameworks. Incentivisation and uptake (Objective 2): to design transnational pathways through which private forest owners and local communities can be economically rewarded for verifiable ecological data via nature-backed digital assets and ReFi mechanisms. Together, these objectives align technical innovation (Objective 1) with behavioural and economic motivation (Objective 2), establishing the groundwork for distributed biodiversity observatories capable of sustaining long-term ecological data flows. Methodological Approach WP 1 develops a blockchain-based data ledger with smart contracts that autonomously manage data registration, access control, and reuse. Metadata and identifiers are immutably recorded on-chain, while primary datasets remain decentralised on contributor-managed nodes. This architecture enables contributors to retain data sovereignty while ensuring transparency and traceability in reuse transactions. WP 2 extends the infrastructure to real-time environmental sensing through the integration of modular Internet ofThings (IoiT)-based microclimate sensors. These devices stream environmental data at high temporal resolution directly into the distributed ledger, forming a Decentralized Physical Infrastructure Network (DePIN) for ecological data. WP 3 links these data streams to the creation of digital twins of forest ecosystems, combining in situ biodiversity observations with satellite and climate datasets to model ecosystem integrity. These models underpin the valuation of nature-backed digital assets, a form of tokenised evidence for ecological performance, providing the data foundation for voluntary biodiversity and carbon markets. Finally, WP4 investigates forest owners’ perceptions, motivations, and barriers to adopting regenerative finance (ReFi)-based conservation mechanisms. Through interviews and a pan-European survey, it explores how varying sociocultural and institutional contexts shape engagement with emerging biodiversity credit schemes, drawing parallels to established Payment for Ecosystem Services frameworks (Kaiser et al. 2021). Significance and Legacy FW3 exemplifies the convergence of data decentralisation, digital sensing, and regenerative economics, a triad capable of transforming how ecological knowledge is produced, verified, and valued. By embedding data provenance and attribution within the infrastructure itself, we addresses long-standing issues of trust and recognition in ecological data sharing. Its incentive mechanisms offer pathways to decouple conservation finance from traditional public funding, potentially scaling stewardship and democratizing data mobilisation across millions of hectares of privately owned forest land. The project’s legacy lies in demonstrating that data infrastructures can be both scientific and economic commons, capable of sustaining biodiversity monitoring through distributed participation. Beyond its immediate technical deliverables, ForestWeb3 contributes to a broader vision of dynamic, self-sustaining ecological data ecosystems that power both global biodiversity frameworks and locally grounded conservation action.
This study aims to analyze the volatility spillovers between Bitcoin and Ethereum, the two main actors in the cryptocurrency market, and altcoins across sectoral and financial groups. Using data from January 1, 2021, to March 6, 2023, the study applied the VAR-based method developed by Diebold and Yılmaz (2012) and measured both directional and total volatility spillovers. The findings show that Bitcoin's volatility largely stems from internal dynamics and spreads to other cryptocurrencies to a limited extent. In contrast, Ethereum is more affected by external shocks and exhibits a stronger volatility spillover across the market. Among altcoin categories, Gaming, Analytics, and DeFi groups were found to be the most influential in volatility transmission, while thematic tokens such as NFT, Web3, and Metaverse were more sensitive to external volatility. In contrast, stablecoins and tokens in the identity and healthcare sectors were found to have relatively low volatility and a more stable structure. These results offer important insights for investors and regulators regarding risk management strategies and portfolio diversification. The study provides a valuable framework for understanding the systematic volatility dynamics within the cryptocurrency ecosystem
Podcasts are a useful educational resource for improving student success, yet traditional methods of podcasting remain inefficient, vulnerable to censorship and deletion, and access-restricted. One approach to addressing these constraints is utilitarian digital pedagogy, which focuses on the use of digital tools to advance education for the greater good. Framed as such, this article outlines the conceptual and theoretical issues underlying how generative artificial intelligence (genAI), Web3, and open access (OA) improve podcasting’s utility relative to the alternatives: manual creation, Web2, and closed access. The article concludes by looking ahead to the major problems—hallucination, technical complexity, and rights management—to overcome in practice.
This article explores the process of building a digital state and the role of public administration digitalization in that context. The relevance of the study lies in the need to enhance governance efficiency through the integration of information technologies. The research aims to provide a comparative analysis of the theoretical foundations of digital governance, international best practices, and their practical applicability. The methodology combines systems analysis with comparative research tools. Findings reveal that digital instruments significantly improve transparency, operational efficiency, and citizen engagement. The scientific novelty of the study is the proposed structural model of interaction between digital governance mechanisms and public institutions. The article also offers practical recommendations for designing and implementing digital strategies in Armenia’s public administration system. The results are applicable to state policy formulation, strategic IT planning, and higher education curricula in the field of public governance and digital transformation.
Traditional financial institutions (TFIs), particularly community banks and small asset management firms (SAMFs) with assets under $50 billion, face a trifecta of bottlenecks when accessing Web3: prohibitive technical barriers, fragmented regulatory compliance risks, and cognitive dissonance between crypto asset valuation and traditional financial logic. In the U.S. market, constrained by multi-agency oversight (SEC, OFAC, FinCEN), the adoption rate of Web3 access among these small TFIs remains merely 5.2% (SIFMA, 2025), far below the 37.8% penetration among large institutions with assets exceeding$500 billion. Leveraging my dual expertise in quantitative finance (CFA Level III) and Web3 multi-chain development (Uniswap V3/V4 protocol experience, daos.world multi-chain DAO incubation), this study constructs a three-dimensional synergistic theoretical framework integrating regulatory adaptation, technical simplification, and valuation migration. A low-barrier access pathway is proposed, centered on the “TradFi-Web3 Connector” system—featuring compliant wallet custody based on EIP-4337 account abstraction and a traditional finance-derived Web3 asset valuation model. Empirical validation across 8 U.S. small TFIs (4 community banks, 4 SAMFs) over an 8-month period (March–October 2025) demonstrates that this pathway reduces the average onboarding cycle from 2.8 months to 9.7 days (82.5% improvement), cuts compliance costs by 61.3% (from $95,400 to$37,300 per annum), achieves a 92.4% investment decision accuracy rate, and maintains a 100% pass rate in SEC compliance reviews with zero regulatory incidents. This research fills a critical gap in low-barrier Web3 access for resource-constrained TFIs, provides a replicable paradigm for the digital transformation of U.S. traditional finance, and empirically validates the synergy between regulatory compliance and technical innovation in cross-ecosystem integration.
Decentralized Finance (DeFi) enables financial services to operate without centralized intermediaries, using smart contracts and blockchain consensus to ensure transparency and trust minimization. While DeFi protocols like Aave and MakerDAO use overcollateralization to mitigate credit risk, this approach creates capital inefficiencies and limits access to borrowers lacking on-chain assets. This paper introduces Inverum, a novel DeFi lending protocol designed to support undercollateralized loans for Web3 businesses and Decentralized Autonomous Organizations (DAOs). Inverum integrates on-chain credit scoring via soulbound tokens, decentralized liquidity pools, and governance-driven incentives to enable trustless, reputation-based lending. The protocol offers a fully composable framework for exploring undercollateralized lending without relying on traditional identity or off-chain reputation systems, contributing a research-ready model for future experimentation and protocol design.
. This study aims to explore the transformation of human resource management in the Web3 era through a bibliometric analysis of global research trends. The research investigates how decentralized technologies, such as blockchain, smart contracts, tokenization, and Decentralized Autonomous Organizations (DAO) reshape human resource management practices toward transparency, autonomy, and efficiency. Using a descriptive qualitative approach combined with bibliometric analysis, data were collected from the Scopus database (2020–2025) and analyzed using VOSviewer to map keyword networks, identify clusters, and determine research evolution. The findings reveal four major research clusters focusing on blockchain applications, human resource analytics, organizational transformation, and smart contract implementation. Results indicate a paradigm shift in human resource management from administrative functions to strategic, technology-driven roles emphasizing digital competence and data transparency. Moreover, the study highlights challenges in privacy, data regulation, and digital literacy as critical barriers to Web3 adoption in human resource systems. The research provides conceptual insights and a framework for understanding human resource management digital evolution, offering implications for policymakers and organizations to design adaptive, decentralized, and human-centered human resource management strategies.
Purpose This study investigates how endorser type (AI-driven virtual vs. human influencers) interacts with product type (NFT vs. physical goods) to shape brand engagement through parasocial relationships. It introduces the concept of digital congruence, examining when fully digital influencers are more effective than their human counterparts in the context of digitally native products. Design/methodology/approach Across three online experiments (Study 1: N = 403; Study 2: N = 663; Study 3: N = 359), this research tests a moderated mediation framework. Study 1 examines the mediating role of parasocial relationships in the influencer–engagement link. Studies 2 and 3 introduce NFT presence as a moderator to evaluate how digital congruence alters consumer response across cultures (UK and China). Findings Human influencers generally elicit stronger parasocial relationships and brand engagement when promoting physical products. However, virtual influencers outperform human endorsers in NFT contexts, driven by enhanced digital congruence. Parasocial relationships mediate the influence of endorser type on engagement, and this mediation is moderated by the presence of NFTs. Practical implications Marketers should align influencer type with product ontology. For traditional goods, human influencers are preferable; for NFTs and other digital assets, virtual influencers yield superior engagement outcomes. Digital congruence enhances parasocial bonds and should be strategically leveraged in Web3 campaigns. Originality/value This research bridges congruence theory and parasocial relationship theory to propose digital congruence as a novel construct. It is the first to empirically demonstrate that alignment between a fully digital endorser and a fully digital product (NFT) enhances psychological resonance and marketing effectiveness.
Digital Marketing and Social Media
Gender, Feminism, and Media
Consumer Behavior in Brand Consumption and Identification
Secure interoperability across heterogeneous blockchains remains one of the most pressing challenges in Web3 with existing bridge protocols vulnerable to both classical exploits and emerging quantum threats. This paper introduces QLink a quantum-safe Layer 3 interoperability protocol that integrates postquantum cryptography (PQC) quantum key distribution (QKD) and hardware security modules (HSMs) into a unified validator architecture. To our knowledge, QLink is the first interoperability framework to combine these mechanisms to secure validator communication proof aggregation and key management. Validators exchange encryption keys through QKD channels, achieving information-theoretic security against interception, while cross-chain proofs are generated and aggregated with NIST-standardized PQC algorithms. Private keys remain sealed inside HSM enclaves mitigating the risk of theft or leakage. Deployed as a dedicated Layer 3 protocol QLink operates independently of Layer 1 and Layer 2 chains providing a scalable decentralized foundation for secure cross-chain messaging and asset transfer. Experimental evaluation using network simulations demonstrates that validator communication overhead remains sub-second while security guarantees extend beyond current bridge architectures to resist both classical and quantum adversaries. By addressing today vulnerabilities and anticipating future quantum threats QLink establishes a practical and future-proof pathway for blockchain interoperability.
Ridwan Yusuf, Andreas Perdana, Febri Sugandi, Untoro Apsiswanto
Smart contract pada platform Ethereum mengelola aset finansial bernilai besar, namun sifat immutable membuat kerentanan kode berdampak permanen sebagaimana ditunjukkan kasus The DAO, Parity Wallet, dan Ronin Bridge. Dua pendekatan pendeteksian kerentanan telah berkembang luas: static analysis yang memeriksa kode sumber atau bytecode tanpa eksekusi, dan dynamic analysis yang menjalankan kontrak pada lingkungan simulasi dengan masukan terstruktur. Keduanya memiliki trade-off kecepatan, cakupan, dan tingkat false positive yang berbeda, namun perbandingan sistematis pada lingkungan pengembangan lokal Indonesia menggunakan alat versi terbaru masih jarang dilakukan. Artikel ini memaparkan rancangan penelitian eksperimental kuantitatif yang akan membandingkan Slither (static) dengan Foundry dan Echidna (dynamic) pada dataset 25 smart contract Solidity yang mencakup lima kategori kerentanan utama: reentrancy, integer overflow, access control, unchecked return values, dan unbounded loop. Metrik perbandingan meliputi precision, recall, F1-score, dan waktu komputasi. Kontribusi yang diharapkan adalah kerangka komparatif yang dapat menjadi rujukan praktis bagi pengembang Web3 Indonesia dalam memilih alat keamanan dan strategi pengujian hibrid yang sesuai dengan tingkat risiko proyek serta sumber daya tim.
Traditional health data infrastructure fragments longitudinal health status into isolated clinical encounters, introduces significant self-reporting bias, and concentrates data ownership among centralized custodians.This paper proposes an institutional research lab architecture-Proof of Health-that treats verified health status as a cryptographically attestable primitive suitable for decentralized trials, data marketplaces, and risk-adjusted health contracts.The architecture integrates three core components: (1) multi-modal longitudinal data collection via remote patient monitoring (RPM), wearable sensors, and structured clinical assessments; (2) privacy-preserving verification using off-chain encrypted storage paired with on-chain attestations and zero-knowledge proofs; and (3) decentralized trial infrastructure supporting hybrid recruitment, telemedicine visits, and electronic patient-reported outcomes (ePROs).We define a standardized "Proof of Health" metric derived from biomarker trajectories, behavioral adherence logs, and imaging-derived phenotypes, versioned using FHIR interoperability standards and blockchain-based metadata provenance.The lab architecture incorporates HL7 FHIR compliance, GDPR/HIPAA-aligned consent automation via smart contracts, and risk-based remote monitoring (RBM) protocols aligned with ICH-GCP guidelines.Initial pilot studies (N = 20-50 participants per cohort) will validate the Proof of Health signal across three use cases: (1) insurance risk stratification, (2) employment wellness contracts, and (3) participation in decentralized science (DeSci) research data marketplaces.Participants retain cryptographic custody of raw data while institutions gain provably valid, tamper-evident health intelligence.We present the system architecture, methodology, preliminary endpoint definitions, and regulatory pathways for pilot and confirmatory trials.This framework aims to resolve the central tension in modern health research: enabling rigorous longitudinal science while strengthening individual data sovereignty and consent transparency.
Syifa Maulida Akmalia, Kodrat Mahatma, Gusti Muhamad Sardana
In today's digital economy, the web has transcended its original role as a communication medium to become a foundational infrastructure for digital transformation. This chapter examines the strategic role of web technologies in enabling scalable, agile, and interoperable systems that support innovation across sectors. It integrates conceptual insights with real-world case studies in government, retail, education, and healthcare to illustrate how the web empowers organizations to enhance customer experience, streamline operations, and enable rapid prototyping. The discussion covers core web technologies—cloud platforms, APIs, frontend frameworks, and backend architectures—and future trends including Web3 and Web 5.0. It also addresses challenges such as legacy integration, cybersecurity, and digital inequality, offering frameworks such as digital maturity models and agile-DevOps approaches for mitigation. By aligning web capabilities with organizational strategy, institutions can create resilient, user-centered ecosystems essential for long-term competitiveness in a connected world.
Probate stands as a bastion of legal formalism, seemingly resistant to the transformative currents of digital innovation that have swept through other domains of American law. While financial transactions, real property conveyances, and contract execution have increasingly begun exploring the use of Web3 technologies such as blockchain and smart contracts, estate and probate law remain tethered to paper-based procedures and rigid execution requirements. Nevada was the first state to provide legal support for Web3 technology, amending its Uniform Electronic Transactions Act statutes in 2017 to recognize blockchain-based transactions as valid and judicially enforceable. Yet despite this progressive legislative framework, the state’s estate and probate laws remain unchanged. What reforms are required to extend this legal recognition of blockchain to testamentary instruments and probate administration? To explore this, I begin in Part I by examining Nevada’s existing statutory framework for traditional paper wills, electronic wills, and probate administration, identifying where these laws diverge from the state’s more progressive legislation governing blockchain-based transactions. In Part II, I introduce the concept of a blockchain will, explain its technical functionality, and discuss how such instruments can be amended, revoked, or rendered obsolete. I then propose specific legislative reforms that could allow blockchain wills to serve as legally recognized alternatives to traditional paper wills, including the creation of a state-managed blockchain will registry that would provide the procedural infrastructure for securely filing, validating, and preserving blockchain wills. To illustrate how these proposals might operate in practice, hypothetical examples modeling blockchain-based testamentary execution and probate are included. Finally, I analyze the policy considerations both for and against reform, examining the legal barriers that must be addressed and the potential benefits this technology could bring to probate courts.
Savings and loan cooperatives play an essential role in promoting financial inclusion and supporting Indonesia's local economy by providing affordable credit and encouraging community-based savings. However, many cooperatives still depend on manual or semi-digital procedures for credit approval, resulting in inefficiencies, delayed loan processing, human errors, and limited transparency. These weaknesses often lead to mismatched capital-to-loan ratios, data inconsistencies, and reduced member trust in cooperative governance. To address these challenges, this study proposes a blockchain-based smart contract framework that automates the credit approval process through secure, rule-based decisionmaking. The research employs the Design Science Research Methodology (DSRM) to design, implement, and evaluate a prototype system developed using Solidity on the Ethereum blockchain, integrated with Web3.js and Metamask for decentralized interactions. The smart contract encodes cooperative business rules, automatically verifies member eligibility, and records transactions immutably on the blockchain ledger. A case study conducted in an Indonesian cooperative demonstrates that the proposed system reduces credit approval time from several days to a few seconds, eliminates manual verification errors, and achieves 100 % transaction success and data consistency. The findings highlight the potential of blockchain and smart contracts to enhance operational efficiency, transparency, and trust in cooperative finance, contributing to Indonesia's digital transformation and offering a scalable model for other community-based financial institutions.
Historical Context and Problem Statement The digital revolution has created two parallel challenges that have resisted comprehensive solutions: Internet Data Transfer Limitations: Despite decades of progress, internet download speeds remain constrained by inefficient protocols that don't adapt to network topology dynamics. Traditional download managers like IDM operate with static segmentation strategies that ignore the quantum-inspired probabilistic nature of network paths. Web3 Liquidity Fragmentation: Decentralized finance (DeFi) suffers from fragmented liquidity across multiple venues, resulting in significant MEV exploitation. As documented by Qin et al. (2021), MEV extraction has cost users over $680 million in 2021 alone, with no comprehensive solution addressing the root cause. These seemingly disconnected problems share a common underlying structure: both involve the transfer of "value" (data or financial assets) across complex networks where efficiency is hampered by non-resonant transmission strategies.
ABSTRACT Phishing attacks in decentralized Web3 systems continue to evolve beyond the detection capabilities of traditional Web2 security models. Existing decentralized authentication systems typically lack either mutual verification or dynamic threat awareness. We present PhishGuard++, a cross‐chain, privacy‐preserving authentication framework that introduces two core innovations: (1) a novel mutual Zero‐Knowledge Proof (ZKP) protocol that validates both users and services using Decentralized Identifiers (DIDs), and (2) a real‐time, on‐chain Graph Neural Network (GNN) threat oracle that assigns phishing risk scores integrated directly into smart contract‐based access control logic. A stake‐based validator reputation system with anti‐collusion incentives further reinforces trust without sacrificing decentralization or privacy. Experimental results on a simulated Arbitrum testnet show a statistically significant 40.4% reduction in phishing success rate across five attack vectors, 98.6% authentication accuracy, and sub‐second latency with gas‐efficient operations. Unlike prior works that independently apply ZKPs, DIDs, or GNNs, this framework offers the first privacy‐preserving, mutual authentication system that combines these technologies with stake‐based economic enforcement and real‐time smart contract enforcement. The novelty lies in the architecture's real‐time threat‐aware access decisions, validator‐linked risk accountability, and practical cross‐chain deployment—an integration not previously achieved.
The web3 applications have recently been growing, especially on the Ethereum platform, starting to become the target of scammers. The web3 scams, imitating the services provided by legitimate platforms, mimic regular activity to deceive users. However, previous studies have primarily concentrated on de-anonymization and phishing nodes, neglecting the distinctive features of web3 scams. Moreover, the current phishing account detection tools utilize graph learning or sampling algorithms to obtain graph features. However, large-scale transaction networks with temporal attributes conform to a power-law distribution, posing challenges in detecting web3 scams. To overcome these challenges, we present ScamSweeper, a novel framework that emphasizes the dynamic evolution of transaction graphs, to identify web3 scams on Ethereum. ScamSweeper samples the network with a structure temporal random walk, which is an optimized sample walking method that considers both temporal attributes and structural information. Then, the directed graph encoder generates the features of each subgraph during different temporal intervals, sorting as a sequence. Moreover, a variational Transformer is utilized to extract the dynamic evolution in the subgraph sequence. Furthermore, we collect a large-scale transaction dataset consisting of web3 scams, phishing, and normal accounts, which are from the first 18 million block heights on Ethereum. Subsequently, we comprehensively analyze the distinctions in various attributes, including nodes, edges, and degree distribution. Our experiments indicate that ScamSweeper outperforms SIEGE, Ethident, and PDTGA in detecting web3 scams, achieving a weighted F1-score improvement of at least 17.29% with the base value of 0.59. In addition, ScamSweeper in phishing node detection achieves at least a 17.5% improvement over DGTSG and BERT4ETH in F1-score from 0.80.