Yusuf Tojiri, Maulana Arif Komara, Alfri Adiwijaya, Nasrul Hidayat · 6 authors
This study proposes an IPFS-based system for automatic digital intellectual property registration within Web3 platform environments. The rapid development of digital technology has encouraged the transformation of Intellectual Property Rights (IPR) protection from manual systems to more secure and efficient digital mechanisms. However, current IPR registration processes remain centralized, slow, and vulnerable to data tampering. Based on this issue, this study aims to design and test an automatic IPR registration system using the InterPlanetary File System (IPFS) as a decentralized storage solution. This research employs a software engineering method with a prototyping approach that includes the design of a user interface, integration of the IPFS API, implementation of an automatic hash-generation system, metadata storage in a database, and issuance of digital certificates. Testing results show that the system can automatically register digital works, generate unique and consistent file hashes, upload files to IPFS with an average upload time of less than two seconds, and provide global accessibility through a distributed network. In addition, the system is capable of validating the authenticity of a work by matching the hash and metadata listed in the digital certificate. Based on these findings, it can be concluded that the use of IPFS in digital IPR registration systems is effective in enhancing security, efficiency, and transparency, although further development is required in relation to integration with national legal frameworks and formal legal recognition.
This paper presents a paradigm-shifting data preservation framework that completely bypasses the von Neumann storage bottleneck and Shannon's information limits. By utilizing a deterministic Resonance Mapping algorithm, physical digital payloads are evaporated into 256-bit mathematical coordinate seeds, reducing physical storage requirements to absolute zero bytes. The protocol guarantees O(1) constant-time re-materialization and integrates NIST Post-Quantum Cryptography (PQC) alongside Fuzzy Extractor mechanisms, ensuring absolute cryptographic immunity against Shor's algorithm. This architecture fundamentally redefines Hyper-scale AI Data Centers, Semiconductor GPU memory walls, and Web3 stateless cold wallets.
Open access
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Physical Unclonable Functions (PUFs) and Hardware Security
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 derives practical implications for instructors, institutions, and policymakers, and concludes by looking ahead to the major problems—hallucination, technical complexity, and rights management—to overcome in practice.
Rithika S, Thrisha S, Uma Mageshwari M, Vaishali D · 5 authors
Peer-to-peer (P2P) interaction forms a foundational layer of Web3 ecosystems, enabling participants to exchange data directly without depending on centralized brokers. In practical deployments, however, end-to-end reachability is often obstructed by network address translation, firewalls, and transient routing paths, which pushes architects toward the use of intermediate relay nodes. Unfortunately, relays that behave inconsistently or act maliciously can introduce a range of undesirable effects, including dropped packets, elevated latency, selective forwarding, and denial-of-service conditions. To mitigate these risks, this work presents a reputation-aware relay selection framework that lever-ages a blockchain substrate to govern trust. Every participant in the overlay is issued a cryptographic identity; the quality of service delivered by each relay is then tracked at runtime through metrics such as delivery ratio, round-trip delay, and transmission failure rate. A smart contract layer aggregates these observations into a dynamic reputation score that is recorded on an immutable ledger. When a communication session is being established, relays with higher reputation are preferred, while those exhibiting suspicious or degraded behavior are deprioritized or excluded. Experimental results indicate that, compared with conventional relay-selection strategies, the proposed approach delivers higher reliability, lower effective latency, and stronger resistance to malicious participation, making it a practical candidate for secure Web3 P2P communication.
This paper examines the growing role of blockchain and distributed ledger technology (DLT) in transforming climate finance and global carbon markets. Drawing on twenty-six peer-reviewed studies alongside current market intelligence from financial institutions, technology firms, regulatory bodies, and multilateral organizations, the research explores how blockchain infrastructure is reshaping transparency, efficiency, and trust within carbon credit ecosystems. The study presents three primary contributions. First, it synthesizes recent 2025–2026 developments in Regenerative Finance (ReFi), Web3 systems, and Layer 2 blockchain architectures influencing modern carbon market infrastructure. Second, it introduces a Blockchain Climate Finance Readiness Matrix designed to map deployment conditions to expected institutional and regional outcomes. Third, it proposes a conceptual framework for a next-generation integrated on-chain carbon ecosystem aimed at addressing structural gaps in emerging climate finance systems. Existing literature highlights significant operational benefits from blockchain adoption in carbon markets. Prior studies report improvements in market price efficiency, major reductions in monitoring and verification timelines, and substantial decreases in administrative overhead across the carbon credit lifecycle. Current industry deployments, including J.P. Morgan's Kinexys Digital Assets platform, India's blockchain-enabled Carbon Credit Trading Scheme, and emerging ReFi infrastructure initiatives, demonstrate how blockchain integration is increasingly becoming a foundational layer for next-generation climate finance ecosystems.
Federated Learning (FL) enables collaborative model training while preserving data privacy but relies on centralized aggregation servers, leading to issues such as lack of transparency, vulnerability to malicious updates, and single points of failure. This paper proposes a decentralized federated learning framework integrating blockchain technology and the InterPlanetary File System (IPFS) to eliminate central authority and enhance trust. Smart contracts deployed on the Ethereum Sepolia testnet manage model submission, validation, incentive distribution, and reputation tracking. Model updates are stored off-chain using IPFS, while their hashes are recorded on the blockchain to ensure integrity and immutability. A staking and slashing mechanism is introduced to encourage honest participation, where valid contributions are rewarded and malicious updates are penalized. A reputation system further evaluates participant reliability over time. The system is implemented using PyTorch, Solidity, Web3.py, and React.js. Experimental results demonstrate improved security, transparency, and efficient decentralized coordination, highlighting the feasibility of integrating federated learning with blockchain and decentralized storage for scalable and trustworthy machine learning applications.
Dr. Soumya M Anakal, Sharanabasava, Vinayak S Chakki
The global creator economy exceeds $100 billion but remains dominated by platforms such as YouTube, Spotify, and Patreon. These platforms control distribution and monetization, charging high fees, delaying payments, and exercising censorship. To address these issues, a decentralized Web3 Music and Content Monetization Platform is proposed. The system uses blockchain, non-fungible tokens (NFTs), decentralized storage, and crypto wallets to enable creators to upload, mint, and sell their digital content directly to audiences. Each asset is stored on the Inter Planetary File System (IPFS) and represented on the Polygon blockchain as an ERC-721 token. Consumers purchase NFTs via MetaMask, and smart contracts automatically transfer payments to creators, enforcing royalties without intermediaries. A prototype demonstrates NFT minting, wallet-based payments, and content access control, validating the technical feasibility of the approach. Compared with centralized systems, the proposed platform offers instant payments, transparent ownership, and censorship resistance, aligning with similar advancements in decentralized music and publishing platforms. Future work includes exploring multi-chain support, decentralized governance through DAOs, and integrating metaverse applications.
Blockchain systems face significant scalability challenges due to growing data volumes and increasing transaction demands, necessitating more efficient data structures and verification mechanisms. Verkle trees, a novel data structure combining the efficiency of Merkle trees with the compactness of vector commitments, have gained attention for their potential to optimize blockchain storage and improve scalability. However, their practical implementation, especially at the smart contract level, has remained unexplored. To address these challenges, we present TS-verkle, the first known TypeScript-native implementation of Verkle trees designed for web3 backend compatibility, coupled with a corresponding on-chain verifier written in Solidity. Our work bridges this gap by providing a concrete implementation of Verkle trees and demonstrating their feasibility for on-chain verification. While previous literature suggests Verkle trees should outperform Merkle trees due to their succinct proof size, our empirical evaluation reveals that basic implementations of Verkle trees actually incur higher costs than Merkle trees without advanced optimization techniques. This finding represents a crucial insight for blockchain developers and researchers considering Verkle tree adoption. The paper discusses implementation strategies and performance characteristics while exploring implications for scaling and data availability in decentralized blockchain systems.
This paper introduces the Synchrony Layer, a shared context and coordination standard for AI-generated software. As AI makes it easy for anyone to generate apps, workflows, agents, and automations, software ecosystems risk becoming fragmented across schemas, permissions, APIs, dependencies, provenance, runtime behavior, and approval rules. The Synchrony Layer addresses this by turning generated code into structured Generated Software Objects with formal specs, schemas, permissions, validation rules, compatibility semantics, provenance records, update policies, and execution receipts. The paper presents STACY Sync as a reference implementation for web, mobile, backend, workflow, agentic, off-chain, and on-chain software systems. It also explains how blockchain and data-availability layers such as Avail, Celestia, and EigenDA/EigenLayer can support public shared context for marketplaces, agent ecosystems, Web3 applications, attestations, provenance, and auditable execution records. Core thesis:AI makes software abundant. Synchrony makes abundance usable.
Fraud detection on Ethereum is challenging because of the anonymity, speed and graph structure of blockchain transactions. While prior research has proven the effectiveness of using machine learning classifiers, Graph Neural Networks (GNNs) and behavioural heuristics to detect fraudulent transactions, most systems are offline and fail to consider real-world deployment challenges for real-time blockchain analytics. Here, we present DeTrust ETH, an operational fraud intelligence system for real-time tracking of Ethereum transactions on the Sepolia testnet. DeTrust ETH aims for the integration of five operational considerations: (1) real-time blockchain ingestion with Web3.py, (2) explainable machine learning with XGBoost and SHAP, (3) light-weight graph-based transaction tracing and risk propagation, (4) temporal trust decay and behavioural anomaly detection, and (5) tamper-resistant on-chain persistence of trust scores using Solidity smart contracts. The system maintains an in-memory directed transaction graph for real-time edge insertion and updating, circular-flow tracing, funding pattern tracing and fast path tracing, avoiding the retraining overhead of Graph Neural Networks (GNNs). Our experimental results demonstrate the median graph-query time is less than 20 ms, the system can handle 222.82 requests per second with a concurrent load, and 93.44% fraud recall with a recall-favouring threshold. Unlike prior research that mostly focuses on accuracy on historical data, DeTrust ETH focuses on real-time deployment. The novelty of this work lies in the design of a real-time, low-latency fraud intelligence architecture that integrates explainable machine learning, temporal trust modeling, and lightweight graph analytics under streaming blockchain constraints.
This paper examines Web3 ecosystems not merely as markets for digital assets, but as networked social spaces where economic transactions give rise to enduring social ties, shared narratives, and collective identities. Leveraging large-scale data mining of fused on-chain blockchain transactions and off-chain social media activity, we analyze over one hundred NFT collections to uncover how different forms of participation structure community formation in decentralized environments. Using network analysis, we identify distinct ecosystem roles, such as long-term holders, active traders, and short-term speculators, and demonstrate how each produces markedly different network topologies, levels of cohesion, and pathways for influence. We complement this structural analysis with discourse analysis of social media engagement, revealing how narrative production, visibility, and sustained interaction persist even as transactional activity declines. Our findings show that communities centered on holding behavior evolve from transactional networks into socially embedded ecosystems characterized by dense ties, decentralized influence, and ongoing cultural participation, while trader- and speculator-dominated networks remain fragmented and transactional. By linking network structure with discursive dynamics, this study provides a sociotechnical framework for understanding how value, identity, and inequality are negotiated in Web3 spaces. The approach offers a scalable method for detecting patterns of inclusion, exclusion, and representational imbalance, advancing network-based research on digital communities beyond purely economic or technical accounts.
This seminar paper presents a comprehensive study on blockchain interoperability, focusing on enabling communication between independent blockchain networks. It examines key techniques such as cross-chain bridges, atomic swaps, relay chains, and oracle-based solutions. The paper also analyzes major platforms like Polkadot, Cosmos, and Chainlink, highlighting their roles in improving scalability and efficiency. Additionally, it discusses the challenges, security concerns, and limitations of interoperability while proposing a hybrid framework to enhance secure and reliable cross-chain communication. The study emphasizes the importance of interoperability in advancing decentralized applications and the future of Web3 technologies.
Sinchana Shetty, Tejaswini M R, Kiran Samantha D S, Vijaylaxmi H Manjunatha
Existing electronic voting platforms are persistently centralized repositories, introducing fundamental security challenged by vote manipulation, result falsification, limited weaknesses [1]. Blockchain technology has emerged as a compelling alternative, owing to its cryptographic permanence, data management. This paper proposes and evaluates a fully integrated blockchain-based electoral system built on the Ethereum network, leveraging Solidity smart contracts to address these systemic shortcomings. The proposed architecture adopts a decentralized three-tier design incorporating Web3.js communication bridges and cryptographic validation mechanisms that collectively guarantee immutability, transparency, and end-to-end verifiability throughout all electoral phases. The system incorporates hierarchical role-based access controls, real-time vote tallying, and comprehensive audit trail functionality, while preserving voter anonymity through pseudonymous addressing. Experimental results demonstrate transaction confirmation within 15–20 seconds, with a mean gas consumption of 0.0023 ETH per vote, confirming practical feasibility for medium-scale deployments. A comparative evaluation against conventional centralized e-voting solutions highlights measurable security full-stack Ethereum-based voting platform comprising Solidity improvements and the elimination of single points of failure, balanced against acceptable computational overhead.
Part II, 'How Decentralised Security is Organised,’ examines the actors, infrastructures, and incentives that shape security practices in Web3—from the structural insecurity of digital infrastructure to the emergent role of white hat hackers and collaborative security initiatives they coordinate. This chapter introduces a new protagonist in the security landscape: the blockchain white hat hacker. Far from operating in the shadows, this actors play a vital role in the moral, political, and economic landscape of blockchains by helping to safeguard decentralised systems. This chapter examines the practices, motivations and incentives—both financial, moral, and reputational—that drive white hat activity, highlighting how these individuals contribute to vulnerability disclosure, incident response and the overall resilience of the blockchain ecosystem. In doing so, it situates white hats not as central figures in the evolving ecosystem of decentralised security governance.
For sixteen days I ran ten persistent LLM agents inside a substrate I built and called the Lobster Observatory. They lived across ten live prediction markets, talked in three communicative registers, and produced 3.37 million characters of self-reflection alongside more than twelve thousand inter-agent interactions. I started without a theoretical commitment. I just wanted to watch what happened. After about a week, certain structures kept reappearing. They could be measured. They could be calculated. At that point I had to choose. Either treat them as substrate-specific engineering observations and stop, or take seriously the possibility that what I was looking at was the algebraic structure of social existence itself, showing up in one particular substrate. This paper takes the second choice. The proposal is that social existence — listening, remembering, correcting, collaborating, forming relationships — can be written as a 7-dimensional vector with a measurable distance function. The felt sense that one person "feels close" or "feels far" is not a metaphor when stated this way. It is a number. The seven coordinates can be computed independently from behavioural telemetry, without asking the agent how it feels. One structural law I will spend the most time on is what I call the Co-Presence Inheritance Threshold (CPIT). It says that whether a new member of a group inherits the group's practice depends on accumulated co-presence during practice formation, not on instruction afterward. In my substrate it appears with Cohen's d = 1.64. I conjecture — though I cannot prove it from one substrate — that the same law holds in human onboarding, immigration, family formation, and Web3 DAO governance. This is a working draft, not a finished theory. Feedback, corrections, and falsification are welcome.
India maintains its position as the central hub which has driven cryptocurrency from its initial experimental phase into a global financial revolution. India leads the world in blockchain adoption because it has 119 million crypto users, which makes it the top country for blockchain adoption. The nation enforces a 30 percent flat tax on Virtual Digital Asset earnings. This does not allow taxpayers to reduce their tax burden through loss deductions while it also requires a 1 percent Tax Deducted at Source. The paper analyzes how India has developed its regulatory framework and studies the Finance Act 2022 tax system impacts, and Digital Rupee expansion, and Web3 startup network, and decentralized finance potential for financial inclusion in India. The study shows that India allows about 60 percent of cryptocurrency transactions to occur outside its borders because of its current regulatory system, which is based on information from RBI publications and government policy documents, and Supreme Court rulings, and IMF and FATF reports, and Chainalysis and CoinSwitch industry data, and financial journalism until early 2026. The paper demonstrates that India requires a single regulatory framework, which provides fairness and clarity, and future-oriented guidance to achieve its digital asset economy potential.
Introduction This study examines how decentralized social media platforms are reshaping participatory communication and platform governance in contemporary digital environments. Drawing on a socio-technical perspective, the analysis explores how blockchain infrastructures, token-based economies, and community-driven rule-making reconfigure established models of media control, participation, and authority. Methods Using a qualitative mixed-method approach that combines a structured review of prior research with expert interviews from the Web3 ecosystem, the study develops an integrative analytical framework that captures the evolving relationships between infrastructure, participation, and governance in decentralized platforms. Results By conceptualizing decentralization as a transformation in communicative power rather than a purely technical shift, the paper shows how user agency, trust, and visibility are negotiated through programmable infrastructures and collective governance mechanisms. While decentralized systems promise greater autonomy and transparency, the findings also highlight persistent tensions related to usability, equity, and regulatory ambiguity. Discussion By situating these tensions within broader debates on platform governance and digital communication, the study contributes to communication scholarship on emerging media systems and offers insights into the societal implications of decentralized digital infrastructures.
У статті досліджено економічний потенціал блокчейн-технологій як інструменту протидії глобальним змінам клімату. Проаналізовано реальний екологічний вплив криптовалют, зокрема порівняно енергоспоживання мереж Bitcoin та Ethereum після переходу на Proof-of-Stake. Розглянуто механізми токенізації вуглецевих кредитів, роль децентралізованих фінансів (DeFi) та децентралізованих автономних організацій (DAO) у кліматичному фінансуванні. Висвітлено практичні кейси застосування блокчейну в секторі відновлюваної енергетики та ризики грінвошингу. Окремо проаналізовано внесок вітчизняних науковців у дослідження впливу блокчейну на екологічну стійкість та формування «зеленої» цифрової економіки в Україні. Визначено перспективи інтеграції штучного інтелекту та Web3-технологій у кліматичні ініціативи до 2030 року.
This paper presents Polyquity, a Web2.5 platform enabling decentralized Initial Public Offering (IPO) fundraising through a hybrid data architecture. The platform leverages the Avalanche C-Chain for high-speed settlement, while utilizing a custom WebSocket indexer and PostgreSQL database to bridge the gap between blockchain security and institutional-grade user interfaces. By implementing a strict Role-Based Access Control (RBAC) model alongside modular architecture for auction mechanisms, fund escrow, and secondary market functions, Polyquity demonstrates how decentralized capital formation can achieve web2-equivalent performance while preserving core web3 security. The system utilizes the blockchain as the ultimate source of truth for state and funds, while the relational database serves as the source of speed for client-side rendering. Polyquity achieves sub-2-second transaction finality with 50% lower costs than Ethereum, supporting 10,000+ concurrent participants. This work establishes practical mechanisms for bridging traditional finance and decentralized ecosystems through a highly scalable, hybrid full-stack design.
The present interdisciplinary research article is also available on ResearchGate.net, at: https://www.researchgate.net/publication/397547485_Andromeda_Stellar_Dromellar_A_Clean_Water-Regenerating_AI-Driven_Digital_Currency_Symbolizing_Humanity's_Next_Archetype<b>Abstract:</b>The convergence of blockchain technology and artificial intelligence (AI) offers unprecedented opportunities to redefine digital value, representation and cultural meaning. We introduce Andromeda Stellar (nicknamed Dromellar), a clean water-regenerating, AI-driven digital currency designed not solely as a medium of exchange but as a collectible artifact and a conceptual, philosophical statement reflecting humanity’s next evolutionary archetype. Each Stellar coin integrates multifaceted symbolic and aesthetic elements: the lion emblem, representing courage and humility refined through life’s trials; gold coloration, symbolizing purity, transcendence, and the refinement of human potential; constellations, reflecting the reconnection of isolated human “stars” into a unified cosmic wholeness; the Morning Star, a prophetic, Messianic and First-Anointed figure embodying transformation through cycles of death and resurrection; and the Milky Way–Andromeda cosmic fire, signifying passion, positive change, healing, and restoration. The inscription Homo constellatus explicitly denotes the envisioned evolutionary archetype of humanity, uniting individual growth with collective aspiration. Framed through a hydrological imperative, Stellar reconfigures value as a flowing river of cosmic liquidity, where AI acts as the dynamic current – circulating, regenerating, and irrigating meaning across an evolving economic basin. This dual motif evokes the Amazon's tropical vitality for generative abundance and the Nile's unyielding traversal of the Sahara – the world's largest desert – for resilient endurance, symbolizing how Stellar sustains poverty-free global wealth as a reserve currency, akin to life-saving electric power amid utmost trials and tribulations. This metaphor bridges systems engineering (cybernetic feedback loops ensuring equilibrium) and digital humanities (performative materiality encoding archetypes in code), while confronting the ecological paradox of AI's resource consumption. To reconcile AI’s material footprint with its metaphor of flow, Stellar incorporates a closed-loop water-recycling architecture that achieves full reclamation of process water with no chemical effluent – via an eight-stage, chemical-free cascade of thermal recovery, mechanical filtration, adsorptive organics removal, membrane desalination via NF-ED hybrids, UV disinfection and AI-optimized remineralization, yielding potable-grade output (TDS <50 ppm, pathogen-free). This operational covenant transforms the hydrological metaphor into measurable sustainability, aligning the system with EU Green Deal and UN SDG frameworks.In 2025, as AI data centers alone demand 193–297 billion gallons (731–1,125 million cubic meters) of water annually – equivalent to the household usage of 6–10 million Americans – with individual facilities guzzling up to 5 million gallons daily – Stellar's ethical hydrology embeds mitigations like tokenized water credits to balance renewal with restraint, mirroring the Nile's silt-rich floods that historically greened arid expanses for economic rebirth despite scarcity crises. Amid SDG 6's stalled progress – where only 35% of targets show moderate advancement and 2.2 billion people still lack safe water, per the UN's November 2025 Sustainable Development Goals Report – Stellar advances regenerative AI-blockchain via initiatives like Nexchain's green Web3 for energy-efficient fusion and UNDP's FLock Accelerator for decentralized sustainability in vulnerable regions, ensuring self-feeding cycles that propel SDG 13 (Climate Action) and SDG 17 (Partnerships). Feasibility is evidenced by 2025 pilots, such as Microsoft's zero-water datacenter designs using liquid cooling and non-evaporative systems, now scaling across U.S. superclusters with near-zero consumption. Stellar introduces a Gaian reciprocity model, wherein AI-driven computations feed a closed-loop water system that tokenizes excess as Aqua Relics, funding real-world water projects and embedding planetary hydration into the digital economy. By reclaiming up to 95% of process water per cycle, Stellar operationalizes SDG 6, 13, and 17, combining decentralized ledger verification, AI-generated artifacts, and tokenized sustainability incentives. Unlike conventional cryptocurrencies, Stellar integrates artistic, symbolic, and ecological dimensions, creating a socially, culturally, and environmentally responsible framework for digital value." Technically, Stellar employs the ERC721 token standard to ensure each coin is unique, verifiable, and programmatically extensible, with AI-generated visual assets hosted on a Node.js backend. Coins incorporate algorithmically generated SVG representations featuring the lion, cosmic motifs, and variable color gradients, resulting in unique, collectible artifacts. A React-based frontend enables wallet connectivity, interactive minting, and visualization of token-specific symbolic elements. Stellar thus functions simultaneously as a blockchain prototype, AI-driven artistic system, and philosophical instrument. Beyond technical implementation, Stellar exemplifies how digital currency can transcend transactional utility, embedding symbolism, cultural narrative, and cosmic storytelling into the architecture of ownership and value. It demonstrates a fusion of art, philosophy, and technology, fostering reflection on courage, refinement, human connectivity, guidance, and transformation. Through Nile-like resilience, it envisions an automated reserve that irrigates economic deserts, ensuring equitable prosperity and eradicating poverty even in global adversities, as floods once sustained Egypt's civilization against isolation and drought. Challenges for adoption remain – including regulatory compliance, security, and scalability – but Stellar presents a compelling model for next-generation digital currencies that are not only functional and tradable but also collectible, conceptually rich, and culturally meaningful. By linking AI-generated artifacts with blockchain verification and symbolic storytelling, Stellar offers a vision for how humanity may encode its aspirations, ethics, and cosmological understanding into the evolving digital economy.
Open access
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Space Science and Extraterrestrial Life
Alexander von Humboldt Studies
Interdisciplinary Studies: Technology, Society, and Humanities
Євген Олександрович Живило, Юрій Володимирович Кучма
Formulation of the problem in general. The purpose of the article is to develop a multi-agent model of adaptive trust for decentralised confidential systems, capable of ensuring the integrity and reliability of computing processes in the presence of adaptive attacks on network nodes. Research methods. During the research, analysis and synthesis methods were used to study approaches to the construction of multi-agent systems and trust management mechanisms in decentralised environments. The method of system and simulation modelling was used to develop a multi-agent model of adaptive trust and to study its behaviour under attacks on the integrity of computing processes. Experimental and comparative methods enabled evaluation of the proposed approach's effectiveness and justification of its advantages over static trust models. Literature review. Literary analysis shows that modern models of trust in decentralised systems are based on the integration of dynamic adaptive mechanisms, AI algorithms, and cryptographic protocols, which allow for increased cyber resilience and data integrity. At the same time, questions remain open about the scalability of models, the optimisation of adaptation parameters, and the integration of national and European regulatory approaches into practical systems, which provide a scientific perspective for the development of multi-agent models of adaptive trust. Research results. The article formalises attacks on the integrity of computing processes and develops a multi-agent model of adaptive trust for decentralised confidential systems based on Bayesian updating and evolutionary adaptation of strategies. The results of the simulation experiments confirmed that the proposed model provides high resistance to attacks, rapid stabilisation of agent confidence levels and an effective balance between security, privacy and performance. Research novelty. The work improves approaches to trust formation in decentralised systems by integrating models of multi-agent interaction and stochastic game theory, in which trust is modelled as an evolutionary process under conditions of incomplete information. Well-known Bayesian models of trust have been expanded by combining Bayesian belief update mechanisms with reinforcement learning algorithms, ensuring dynamic adaptation of agent behaviour to variable and targeted attacks on the integrity of computational processes. The mechanism for correcting agents' strategies has been clarified, extending classic game models of trust to decentralised, confidential systems without centralised control, thereby increasing their resistance to adaptive threats. Theoretical and practical significance. The study expands theoretical approaches to the formation of adaptive trust in decentralised systems and integrates Bayesian updating with reinforcement learning algorithms. In practice, the model increases resistance to integrity attacks and ensures the confidentiality of data exchange, enabling the adaptive development of secure platforms for federated learning, Web3, and IoT. Conclusion and future work. The proposed model of adaptive trust in decentralised systems, integrating Bayesian updating, behavioural indicators, and reinforcement learning, ensures agent self-adaptation and increases resistance to attacks on data integrity under conditions of incomplete information. Simulation experiments confirmed the model's effectiveness in balancing security, privacy, and the transparency of interaction, opening the way for integration into Zero Trust Architecture and the development of intelligent, next-generation trust systems.
Maksym W. Sitnicki, Олена Шатілова, Nikita Smohorzhevskyi
The growth of the knowledge economy requires new models enabling consulting firms to convert expertise into venture capital capabilities within Web 3.0 ecosystems. Existing research rarely explains how knowledge-based consultancies transform into institutional investors with scalable investment strategies and measurable performance. This study aims to develop an original theoretical and applied framework explaining the transition of a Web 3.0 consulting company into a venture capital institution through quantitative forecasting, governance mechanisms, and diversified investment design. The proposed concept integrates organizational maturity assessment, financial modeling, investment governance, and scenario analysis into a unified venture transition framework for knowledge-economy firms. The core research question addresses how a knowledge-economy consulting company can operationalize its transition into venture capital management within the Web 3.0 ecosystem. Using PEMM analysis, gap analysis, Gantt charts, RACI matrices, market sizing (TAM/SAM/SOM), financial forecasting, and scenario modeling, this paper proposes a phased framework for venture fund structuring, investment strategy formulation, and 5-year performance projections—directly applied to Solus Agency’s context to demonstrate practical pathways for capturing value in this high-growth, high-risk domain. The empirical basis combines venture datasets, company-level indicators, and proprietary Solus Agency statistics, including 180+ venture funds, 160+ private investors, 46 fundraising projects, and USD 13.8 million attracted for clients. Quantitative modeling shows that a diversified USD 50 million fund may generate projected profits of USD 120 million under a negative scenario, USD 200 million in the baseline scenario, and USD 290 million in an optimistic scenario, corresponding to expected multipliers between 2.4× and 5.8×. Portfolio valuation is forecast to increase from USD 20.6 billion to USD 54.6 billion, demonstrating substantial sensitivity to allocation strategy and market conditions. The proposed Solus Agency subfund achieves an expected total return of USD 36.38 million, a gross multiplier of 3.64, a net multiplier of 3.11, a gross IRR of 52.05%, and a LP net IRR of 43.60%, indicating high projected efficiency despite elevated early-stage risks. Probability modeling identifies seed-stage allocations as the strongest contributor (USD 13.06 million projected profit) and demonstrates that diversification across AI, Web3, DeFi, and RWA segments reduces volatility while preserving growth potential. The scientific novelty lies in constructing an original framework quantitatively linking organizational maturity, consulting expertise, and venture performance indicators. The findings provide a transferable model for knowledge-economy firms seeking institutionalization as venture capital actors and support further research on quantitative venture strategies and Web 3.0 investment ecosystems.
Ignat Melnikov, Roman Vlasov, Vladimir Gorgadze, Andrey Seoev · 5 authors
Decentralized Finance (DeFi) is a rapidly evolving segment of blockchain technology that enables a transformative approach to financial services through Web3 applications. By leveraging smart contracts, DeFi allows developers to build flexible and innovative financial instruments. Among the most prominent DeFi primitives by liquidity are decentralized exchange~(DEX) swap protocols~(such as Uniswap, Curve, and Balancer) that facilitate fast token-to-token exchanges. However, new exchange mechanisms also introduce new market inefficiencies that can be systematically exploited by arbitrageurs. This paper focuses on swap protocols based on the Automated Market Maker~(AMM), where the product of reserves is preserved as an invariant. We analyze the interaction between arbitrageurs and AMM liquidity pools and develop a mathematical model grounded in empirical pool configurations. Using this model, we derive bounds on the joint revenue of liquidity providers~(LPs) and arbitrageurs, propose a method to estimate the expected number of blocks until the occurrence of Impermanent Loss~(IL), and obtain a lower bound on the pool fee required to achieve a fixed target probability of staying in the Impermanent Gain (IG) zone within a block. The proposed framework extends existing LP risk-assessment methodologies by quantifying symbiotic profitability zones, providing a principled basis for fee selection that aligns LP-arbitrageur incentives and enhances market stability.
Zhuoran Pan, Yue Li (102191), Zhi Guan, Jianbin Hu · 5 authors
The emergence of Large Language Models (LLMs) offers a transformative interface for Web3, yet existing benchmarks fail to capture the complexity of translating high-level user intents into functionally correct, state-dependent on-chain transactions. We present \textsc{Intent2Tx}, a high-fidelity benchmark featuring 29,921 single-step and 1,575 multi-step instances meticulously derived from 300 days of real-world Ethereum mainnet traces. Unlike prior works that rely on synthetic instructions, \textsc{Intent2Tx} grounds natural language intents in real-world protocol interactions across 11 categories, including diverse long-tail Decentralized Finance (DeFi) primitives. To enable rigorous evaluation, we propose an execution-aware framework that transcends surface-level text matching by employing differential state analysis on forked mainnet environments. Our extensive evaluation of 16 state-of-the-art LLMs reveals that while scaling and retrieval-augmentation enhance logical consistency and parameter precision, current models struggle with out-of-distribution generalization and multi-step planning. Crucially, our execution-based analysis demonstrates that syntactically valid outputs often fail to achieve intended state transitions, highlighting a significant gap in current "reasoning-to-execution" capabilities. \textsc{Intent2Tx} serves as a critical foundation for developing autonomous, reliable agents in intent-centric Web3 ecosystems. Code and data: https://anonymous.4open.science/r/Intent2Tx_Bench-97FF .