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 .
본 연구는 콘텐츠 과잉과 플랫폼 종속성이라는 전통적 광고 모델의 한계를 극복할 대안으로 부상한 Web3 기반 참여형 브랜딩의 수용 양상을 탐색하기 위해, 대표적 NFT 프로젝트인 Azuki의 유튜브 댓글을 실증적으로 분석하였다. Azuki는 홀더가 IP 확장에 기여하는 ‘Enter The Garden’ 시리즈를 통해 소비자를 브랜드 서사의 공동 창작자로 격상시키는 혁신적 모델을 제시한다. 이에 본 연구는 161개 영상의 46,647개 댓글을 대상으로 구조적 토픽 모델링(STM)과 사회연결망 분석(SNA)을 수행하였다. 분석 결과, 시청자 담론은 콘텐츠의 미학성에 반응하는 ‘외재적 팬덤’과 프로젝트 가치에 관여하는 ‘내재적 공동체’가 공존하는 이중적 구조를 보였으며, 내부 용어가 상징적 경계로 기능하였다. 네트워크 분석에서는 연결망 밀도가 극히 낮은 ‘방사형 공동체’ 특성이 드러나, 구성원 간 직접 소통보다는 브랜드를 구심점으로 한 개별적 상호작용이 주를 이루는 것으로 나타났다. 한편, 영향력 분석에서는 비판적 댓글이 오히려 커뮤니티의 핵심 가치를 옹호하는 집단적 방어 기제를 촉발하여 내재적 결속을 강화하는 현상이 확인되었다. 본 연구는 성공적인 NFT 브랜딩이 참여권으로서의 가치 설계, IP 무결성 유지, 팬덤과의 신뢰 구축에 있음을 시사하며, 전통 미디어 기업의 IP 확장 전략에 실질적 통찰을 제공한다.
A decentralised Web3 framework for ecological landscape Design in Urban Parks Based on AI-aided Virtual Interaction. The framework links multi-source park data, a spatial ecological graph, AI co-design, and smart-contract governance so that design states, feedback records, and voting outcomes remain verifiable, with large scene assets stored off-chain. After ten iterations of the three renewal modes, its composite ecological benefits index was 0.95, with a mean habitat suitability value of 0.89 for all six parks; There was a relatively average gain rate of +56% in visitor satisfaction and +50% in carbon storage between new and old buildings. At the peak of five thousand simultaneous user access, the system's response time per unit of operation were respectively eight-two (ms), four-hundred-eighty-nine (-81%), forty-seven-fortytwo-six(-77%). Ablation test results show: without consensus confirmation, eco-enforcement and virtual reinforcement the effectiveness decreased by 4.8-12.7 per cent. Although the form is not perfect yet; still provides an operational path to join ecological Design and participatory Governance.
Artificial intelligence (AI) is rapidly transforming the music industry by reshaping creative processes, lowering barriers to entry, and redefining governance structures. This article examines AI’s dual role as both a catalyst for innovation and a potential source of artistic and economic disruption. On the creative front, AI-assisted tools enable rapid composition, personalized learning, and new forms of experimentation; however, they also risk homogenization, cognitive dependency, and diminished originality. From the standpoint of accessibility, AI democratizes music production by reducing costs and technical barriers, yet disparities in digital access and algorithmic visibility persist. Governance challenges are equally significant, as AI-driven platforms influence discovery, revenue distribution, and authorship attribution, often reinforcing existing power asymmetries. To address these concerns, this article evaluates emerging decentralized frameworks, particularly blockchain and Web3 systems, which offer mechanisms for transparent attribution, equitable royalty distribution, and participatory governance. These technologies provide a potential counterbalance to centralized algorithmic control, enabling more artist-centered ecosystems. Ultimately, the impact of AI in music depends not on the technology itself but on the institutional structures guiding its use. Thoughtful integration can position AI as an augmentative tool that enhances human creativity while preserving artistic integrity and equity.
ABSTRACT Forgery of academic and professional certificates remains a major concern across institutions. Traditional centralized systems are prone to manipulation and single points of failure. This work presents a blockchain-based certificate issuance and verification platform developed using Spring Boot and the Ethereum Sepolia test network. The system supports multiple organizations where issuers register and are approved by an administrator before generating certificates. Each certificate is assigned a unique identifier, and a SHA-256 hash of its data is stored on the blockchain through smart contracts. The platform also automates PDF certificate creation with embedded QR codes and sends them via email. Additional features include bulk certificate generation, revocation support, and public verification without requiring a blockchain wallet. Experimental observations indicate an average issuance time of around 4 seconds and verification within 1.5 seconds. Keywords: Blockchain, Ethereum, Smart Contracts, SHA-256, Certificate Verification, Spring Boot, Web3j, PDF Automation
Deepa Parasar, Dr. Priyanka Mishra, Aman Kumar Hamilton, Snigdha Madhab Ghosh, Dhanashree Rohan Kedare, Dr. Atowar ul Islam
Among the most influential technologies that predetermine the current digital society, artificial intelligence (AI) and blockchain have emerged as fast as the digitalization of technologies. This review examines the conceptual and practical implications and applications of AI and blockchain with particular attention to how the two can be used in the framework of digital governance, cybersecurity, and socio-cultural change. The analysis synthesizes existing literature to explore how AI enhances data processing, predictive analytics, and automated decision-making, while blockchain strengthens transparency, decentralization, and data integrity in digital systems. Their integration is shown to support more efficient governance frameworks, improved policy decision-making, secure digital infrastructures, and reliable identity management. At the same time, the review highlights broader societal impacts, including changes in digital trust, ownership structures, and creative and media industries. Despite these opportunities, several challenges remain, including governance fragmentation, ethical concerns, privacy risks, and limitations related to interoperability and institutional readiness. New research directions are also outlined in the form of trustworthy and explainable AI, sustainable technological infrastructures, and the adoption of AI and blockchain systems of Web3 and decentralized digital ecosystems. Altogether, AI and blockchain convergence is an important change in the structure of the digital space, and it will need harmonized governance structures and responsible innovation to establish safe, transparent and inclusive digital societies.
Abstract This study presents a structured dataset of blockchain-registered artificial intelligence agents under the ERC-8004 standard on Ethereum. The dataset integrates on-chain identity records, minting transactions, transfer events, reputation summaries, and individual feedback records, together with resolved off-chain metadata where available. Data were collected from Ethereum mainnet using Web3 RPC queries and processed into tabular form to enable reproducible analysis. The dataset covers 10,000 agents within a defined block range and includes both event-level records and aggregated summaries. It enables empirical research on agent identity formation, reputation systems, service exposure, and early-stage decentralized AI ecosystems. This resource supports studies in blockchain analytics, decentralized trust infrastructure, and the emerging agentic economy.
The rapid growth of cloud computing has significantly transformed the way digital data is stored, managed, and accessed, enabling efficient sharing of information across distributed environments; however, this advancement introduces serious concerns related to data security, privacy, and trust, particularly when sensitive information is involved. Many cloud-based systems rely on centralized architectures, which increase the risk of single points of failure, unauthorized access, data tampering, and limited transparency in tracking data activities. These systems often depend on basic encryption techniques without strong auditing or verification mechanisms, making them vulnerable to insider misuse and external cyber threats, while the absence of immutable records reduces accountability and weakens user confidence. Such limitations highlight the need for a secure and transparent data-sharing framework that ensures confidentiality, integrity, and traceability of data transactions. To address these challenges, the proposed system introduces a secure cloud data sharing model developed using the Django framework, integrating Elliptic Curve Cryptography (ECC), blockchain technology, and the InterPlanetary File System (IPFS) to enhance data protection and decentralization. In this approach, ECC is used to generate cryptographic keys and encrypt user files before storage, ensuring that only authorized users can decrypt the data using the corresponding private key. The encrypted files are stored using IPFS for distributed and content-addressable storage, while file metadata such as username, filename, and timestamp is recorded on the blockchain through smart contracts using Web3, providing a decentralized and tamper-resistant record of all transactions. The system also supports user registration, authentication, secure file upload, and controlled file download functionalities, ensuring secure access and traceability. During file access, encrypted data is retrieved from IPFS and decrypted using ECC to maintain end-to-end security. By combining cryptographic encryption, decentralized storage, and blockchain-based verification, the proposed system enhances data confidentiality, prevents unauthorized modifications, and establishes a reliable and transparent framework for secure cloud data sharing.
E. Sravanthi, Pabbathi Laxmiprasanna, Mulukutla Jahnavi, Kancharla Kritika Reddy
The increasing reliance on digital systems in law enforcement has emphasized the need for secure, transparent, and reliable mechanisms to manage crime evidence. In existing systems, evidence management is typically handled through centralized databases and manual record-keeping, where crime reports, officer details, and evidentiary materials are stored in a single controlled environment. This approach introduces critical challenges such as data tampering, unauthorized access, loss of sensitive information, and lack of transparency, which can weaken trust and complicate legal proceedings. Furthermore, storing evidence in physical formats or unsecured digital systems makes it difficult to ensure authenticity and maintain a proper Chain of Custody (CoC). These limitations highlight the necessity for a system that ensures data integrity, traceability, and secure verification. To overcome these issues, the proposed framework adopts a decentralized architecture using Blockchain technology and Smart Contracts to provide immutability, transparency, and enhanced security of evidence records. The system leverages Ethereum for decentralized data storage, Web3 for enabling interaction between the application and the blockchain network, and Django as the web framework for managing the user interface, file handling, and administrative functionalities. Authorized officers can securely upload, access, and manage evidence, while administrators can monitor and verify transactions in real time. Each evidence record is assigned a unique identifier and permanently stored on the blockchain, preventing unauthorized modification and ensuring a verifiable audit trail. Although the system does not utilize Machine Learning (ML) or Deep Learning (DL), it effectively employs smart contracts-based automation for secure evidence tracking, thereby improving accountability, legal reliability, and operational efficiency.
Drug repurposing has emerged as an effective strategy in modern healthcare, enabling researchers to discover new therapeutic uses for existing drugs while significantly reducing development time and cost. Traditional drug discovery methods rely heavily on manual laboratory experiments, expert analysis, and prolonged clinical trials, making the process slow, expensive, and limited in scalability. These approaches struggle to handle complex and high-dimensional biomedical data, leading to delayed insights and reduced efficiency. With the rapid growth of healthcare data, there is an increasing need for intelligent and automated systems that can efficiently analyze drug characteristics and predict alternative therapeutic applications. Additionally, conventional systems often lack transparency and strong security mechanisms, making clinical data vulnerable to tampering and reducing trust in research outcomes. To address these challenges, the proposed framework integrates Machine Learning (ML), Deep Learning (DL), and Blockchain technologies to develop a secure and intelligent drug repurposing system. The framework employs Random Forest (RF) as a baseline model and a Two-Dimensional Convolutional Neural Network (CNN2D) as an advanced model to improve prediction accuracy. The CNN2D effectively captures complex feature patterns in structured drug data, enabling precise identification of potential new disease treatments. Furthermore, Web3-based Blockchain technology ensures secure storage of user data, clinical interactions, and experimental records by providing immutability, transparency, and data integrity. By combining Artificial Intelligence (AI)-driven analytics with Blockchain-based security, the system enhances prediction performance, automates decision-making, and ensures reliable data management, offering a scalable and efficient solution for accelerating drug discovery and supporting healthcare innovation.
Kunal Kumar, Mohammad Malik, Gujju Koushik, Nujetti Abinandhan
The evolution of blockchain technology has introduced innovative approaches for managing digital assets and transforming fundraising models through Non-Fungible Tokens (NFTs). However, many existing charity platforms continue to operate on centralized systems that restrict transparency, limit accountability, and fail to provide donors with verifiable proof of their contributions. In such systems, donors often have minimal visibility into fund utilization, and there is no direct linkage between their contributions and any traceable digital asset. Moreover, traditional charity and auction mechanisms rely heavily on intermediaries for transaction validation, data management, and operational control, making them susceptible to data manipulation, reduced auditability, and diminished user trust, while also lacking mechanisms to encourage active participation. To address these limitations, this research proposes a decentralized charity auction framework that integrates Blockchain technology with NFTs to ensure secure, transparent, and verifiable transactions. The system is developed using the Django Web Framework and leverages Web3 Technology along with Smart Contracts to automate and manage auction processes. Each auction item is uniquely tokenized as an NFT, guaranteeing authenticity and non-replicability. Users can register as donors or auction organizers, create NFTbased auctions, and participate through bidding or direct contributions. All transactions are permanently recorded on the blockchain, and NFT ownership is automatically transferred to the highest bidder or contributor, serving as a verifiable digital proof of participation. By removing intermediaries and ensuring immutable record-keeping, the system enhances trust, strengthens security, and introduces an incentive-driven participation model, thereby improving transparency, accountability, and efficiency in modern charity and fundraising ecosystems.
Abstract Web3 infrastructure has demonstrated that decentralized coordination is technically feasible. Yet the dominant governance model — token-weighted voting — produces structural concentration of decision-making authority over time, and has not proved well-suited to real-world economic coordination. This paper argues that the missing element is constitutional ownership geometry: a structural arrangement of bounded roles and non-dilutable stakeholder balance that persists as participation evolves. We introduce the Vessel Compartment System (VCS), developed within the Mycelia Inclusive Networks (MIN) framework, as one such approach. VCS distributes governance authority across fixed ownership compartments representing distinct stakeholder roles — community participants, operators, capital providers, and ecosystem partners — each non-dilutable relative to the others. Participants within compartments may change; the balance among compartments does not. Web3 infrastructure provides the enforcement and portability layer this model requires: smart contracts encode compartment boundaries, tokenized roles enable exit without requiring dissolution of institutional structure, and composable systems support cross-vessel coordination. Together, these features allow governance to remain internally stable while evolving externally through participant migration across structurally stable governance units. The paper situates VCS within established governance theory, contrasts it with token-weighted and procedural governance models, and examines its implications for real-world economic coordination and Web3 system design. Keywords: Web3 governance, token-weighted voting, decentralized autonomous organizations, ownership geometry, Vessel Compartment System, constitutional governance, exit-driven evolution, real-world economic coordination, multi-stakeholder governance
Wahida Mansouri, Abdulrahman M. Qahtani, M. M. Kamruzzaman, Anandhavalli Muniasamy · 6 authors
The evolution of 6G networks brings unprecedented connectivity and processing capabilities to Internet of Things environments, yet it also raises more challenges in data security, intrusion detection, and computational efficiency. In this paper, a complete end-to-end framework with the inclusion of Artificial Intelligence, blockchain technology, and novel encryption techniques is proposed to address these challenges in 6G-IoT networks. Then, the AI-Powered Cybersecurity Events Dataset is utilized first, wherein network traffic is normalized through Min-Max normalization to normalize heterogeneous features to a uniform scale. A Gated Recurrent Unit-based neural network is then trained on this normalized data to detect real-time intrusions by learning complex temporal dependencies. Upon detecting anomalies, a blockchain layer is called to execute smart contracts that apply automatic security measures, e.g., quarantining affected nodes. For efficient processing, the architecture accommodates GRU-assisted task offloading optimization on a multi-factor delay, energy, and network load optimization model. Blockchain smart contracts manage load balancing and delegation verification autonomously without any central authority. Homomorphic encryption and proxy re-encryption also ensure data confidentiality in edge computing and secure multi-party computation. All encryption and task offloading operations are permanently stored onto the blockchain, ensuring system-wide transparency and auditability. Federated learning support is built-in to enable privacy-preserving decentralized AI training from distributed edge nodes. The entire framework is implemented in Python using TensorFlow/Keras for the GRU model and web3.py for blockchain-related interactions. Experimental measurements demonstrated the efficiency and stability of the system by exhibiting a percentage of accuracy of 98.9% in intrusion detection, justifying the applicability for future 6G-IoT secure and scalable operations. The experiments utilize the AI-Powered Cybersecurity Events Dataset containing approximately 1.5 million network flow records with class distribution of 52% benign traffic, 21% DoS, 15% probing, and 12% privilege escalation events.
Munaganti Anjali, Arra Nanda Kishore, Sirnapally Mithesh, Mr Lodangi Prabhat
Abstract—The crowdfunding sites that are in use today make use of a centralized system in which the funding and validation of crowdfunding campaigns are done by an authority figure. This has resulted in higher transaction fees and a lack of transparency in the way the funding is being done by donors. This paper aims to propose a Decentralized Crowdfunding Platform using blockchain technology to overcome the current challenges. A new crowdfunding system based on smart contracts using Ethereum is proposed. This new system will ensure a reliable environment for executing smart contracts. A new crowdfunding system based on smart contracts using Ethereum is proposed. This system will have a Startup Verifi-cation process and an Iteration-Based Fund Release process. In the current crowdfunding system, crowdfunding sites release the funds in bulk to the startup. In the new system that is being proposed, the funds will be released in stages. A new system of voting will also be implemented in the new system. This will enable donors to vote based on the cryptographic proofs and reports that are presented by the startup. The software development framework of the platform is based on an effective decentralized technology stack such as Solidity for smart contract development and execution, Hardhat for software development and testing, and React.js combined with Web3.js for front-end interface development. The incorporation of the blockchain technology stack guarantees that all financial transactions are transparent, secure, and tamper-proof. The efficacy of the proposed decentralized approach is measured by how effectively it avoids the costs of intermediaries, is auditable in real-time, and is democratic in nature for all donors. Index Terms—Blockchain Technology, Ethereum, Smart Con-tracts, Solidity, Decentralized Finance (DeFi), Crowdfunding, Decentralized Autonomous Organization (DAO), Iteration-Based Funding, Milestone Verification, Web3.js, Hardhat, Metamask, Trustless Execution, Cryptographic Transparency, Digital Wallet Authentication.
This research presents a blockchain-enabled freelancing platform that integrates smart contract-based escrow, decentralized identity, and intelligent freelancer matching to promote trust, transparency, and automation in digital labor markets. The system uses an Ethereum-compatible smart contract called Freelance Escrow, which manages the funding of projects securely, restricts interactions between employers and freelancers to a few specific roles, and automates the release of payments based on the verifiable completion of work. A Python-based blockchain interface developed using Web3.py is used to deploy contracts, sign transactions, and retrieve the current states, while a Streamlit front end provides authentication for user, project, and wallet operations. The platform includes a TF-IDF similarity model that matches freelancers to projects based on relevant skills and semantic similarity, as well as a structured database using SQLite, in which all users, profiles, and project metadata are stored. Comprehensive analysis reveals that the application has strengths in automation, transparency, and enforcement of workflow, while addressing privacy concerns around private key handling, file path inconsistencies, and Web3 library compatibility. The research demonstrates a working end-to-end architecture for decentralized freelance contracting and establishes a foundation for building further secure, scalable, and trust-preserving digital marketplaces.
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The rapid expansion of blockchain infrastructures, Web3 architectures, and immersive metaverse environments has reignited calls for a Universal Code of Digital Ethics. International organizations, technology leaders, and multilateral forums increasingly advocate for global standards capable of guiding decentralized innovation toward inclusion, transparency, and social good. Yet the normative ambition of universality confronts a structural contradiction: digital access, connectivity quality, and technological literacy remain profoundly unequal across the Global South.Ethical frameworks for Web3 and the metaverse often presuppose a baseline of connectivity, computational capacity, and institutional stability that large segments of humanity do not possess. The COVID-19 pandemic amplified these asymmetries, accelerating digital transformation in high-income countries while deepening infrastructural gaps elsewhere. Concurrently, geopolitical tensions and emerging techno-nationalist strategies have repoliticized digital infrastructure as a domain of strategic competition rather than global solidarity.This Opinion article argues that any claim to a "universal" digital ethics framework is normatively fragile unless it incorporates a structural critique of global capitalism, technological acceleration, and asymmetrical power. Drawing on critical theory-particularly Herbert Marcuse's concept of the "one-dimensional man"-as well as Marxian analyses of technology and capital, I contend that ethical discourse risks becoming ideologically functional to market expansion if it fails to address material inequalities in connectivity and digital capability (Marcuse, 1972;Marx, 2005;García Ramírez, 2021).proposals but also problematizes the concept of universality itself as a normative and political construct.Global ethics initiatives often frame digital transformation as inherently democratizing. Blockchain is described as decentralized, Web3 as user-empowering, and the metaverse as participatory. However, decentralization at the protocol level does not necessarily translate into equitable access at the societal level.In regions of the Global South, access to stable broadband remains limited, mobile data costs are disproportionate to income, and digital literacy gaps persist. Under such conditions, the ethical vocabulary of autonomy, self-sovereign identity, and tokenized participation becomes aspirational rather than operative.Marx's analysis of technology as a force embedded within relations of production remains instructive. Technology is not neutral; it is shaped by capital accumulation dynamics (Marx, 2005). Fumikazu (1983) similarly emphasized that technological evolution must be understood historically and politically. When applied to Web3 ecosystems, this suggests that blockchain infrastructures operate within global financial logics that may reproduce, rather than dissolve, structural dependency.Contemporary Science and Technology Studies (STS) and critical philosophy of technology further reinforce this perspective. Feenberg (1999) argues that technology is not merely instrumental but socially constructed and politically conditioned, shaped by dominant interests yet open to democratic transformation. Similarly, Yuk Hui (2020) challenges the presumed universality of technological rationality, proposing the concept of "technodiversity" to account for plural technological trajectories rooted in different cultural and cosmological traditions. These perspectives suggest that any ethical framework for digital technologies must recognize the multiplicity of socio-technical realities rather than assume a homogeneous global condition.Thus, a universal code of digital ethics risks functioning as what critical theory would describe as ideological abstraction-detached from the material preconditions required for ethical agency.Herbert Marcuse's One-Dimensional Man (1972) provides a compelling lens through which to interpret contemporary digital governance. Marcuse argued that advanced industrial societies generate a form of technological rationality that integrates dissent by absorbing it into the logic of efficiency and consumption.In the context of Web3 and the metaverse, ethical discourse may become one-dimensional when it focuses on procedural compliance (privacy standards, transparency metrics, algorithmic audits) while neglecting structural exclusion. The language of inclusion becomes embedded within market expansion strategies. As Daum (2018) argues, digital capitalism increasingly converts users into capital itself-data, attention, and participation become monetizable assets.From a constructivist perspective, technologies such as blockchain are not inherently emancipatory but acquire meaning through their social embedding (Bijker, 1995). This implies that ethical claims about decentralization and empowerment must be evaluated in relation to the socio-economic contexts in which these technologies are deployed. Without such contextualization, ethical discourse risks overstating the transformative potential of technological architectures. This dynamic is particularly visible when global institutions promote digital entrepreneurship and blockchain adoption in developing regions without parallel investments in public infrastructure, education, and regulatory sovereignty. The rhetoric of empowerment may conceal asymmetric dependency.Cañas Quirós (2023) emphasizes that ethics cannot be separated from political structures; morality detached from power analysis risks legitimizing unjust arrangements. In this sense, digital ethics frameworks must confront the political economy of connectivity rather than merely codify behavioral norms for technology developers.Digital governance is increasingly entangled with geopolitical competition. Infrastructure financing, cloud sovereignty, semiconductor supply chains, and cybersecurity alliances shape technological ecosystems. In this context, international organizations often advocate regulatory harmonization to "facilitate innovation" and "reduce market friction".While harmonization may lower barriers for cross-border digital services, it can simultaneously constrain policy autonomy in developing nations. Ethical frameworks that prioritize market efficiency risk subordinating universal connectivity goals to investor confidence and capital mobility.García Ramírez (2021) calls for a "Marx in the South," reinterpreting technology through the lens of rights, education, and structural inequality. From this perspective, Web3 adoption without universal broadband is analogous to building virtual property rights atop infrastructural scarcity. The promise of decentralized finance or immersive governance becomes utopian-or dystopian-when foundational digital rights remain unrealized.The acceleration principle of technological evolution -where innovation in wealthy nations compounds exponentially-renders access in peripheral regions inversely proportional to global advancement. Ethical frameworks that ignore this asymmetry may inadvertently normalize a tiered digital citizenship.The assumption that a single set of ethical principles can be universally applicable across diverse socio-cultural and technological contexts has been widely debated. From decolonial and pluralist perspectives, ethical frameworks are historically situated and epistemically conditioned (Escobar, 2018). What is considered "ethical" in one context may not translate directly into another, particularly when technological infrastructures, cultural values, and political systems differ significantly.In this sense, the concept of a Universal Code of Digital Ethics may be inherently paradoxical. Rather than a fixed and homogeneous set of principles, digital ethics may need to be understood as a plural and adaptive framework, capable of accommodating different technological ontologies and social priorities. This does not imply abandoning normative aspirations, but rather rethinking universality as negotiated, situated, and contingent.If a global digital ethics framework is to be normatively defensible-whether universal or plural-it must integrate structural and contextual dimensions:If universality is to be normatively defensible, digital ethics must integrate at least five structural components:If universality is to be normatively defensible, digital ethics must integrate at least five structural components:1.Material Preconditions Clause: Ethical standards should explicitly recognize connectivity, affordability, and digital literacy as prerequisites for meaningful participation.Political Economy Transparency: Frameworks must disclose how market incentives shape technological deployment.Geopolitical Reflexivity: Digital governance should account for power asymmetries between states and corporations.Public Infrastructure Commitment: Ethical guidelines must prioritize universal broadband as a public good, not merely a commercial opportunity.Critical Participation Mechanisms: Inclusion must extend beyond tokenized representation toward substantive decision-making capacity.5.6. Epistemic Pluralism: Ethical frameworks must recognize diverse knowledge systems, cultural values, and technological imaginaries, particularly from the Global South.Such principles align ethics with transformative social justice rather than technocratic governance.The aspiration to develop a Universal Code of Digital Ethics for Web3 and the metaverse is commendable. However, without structural critique, universality risks becoming rhetorical. Critical theory reminds us that technological systems embed power relations (Marcuse, 1972). Marxian perspectives reveal how capital shapes technological deployment (Marx, 2005). Contemporary analyses from the Global South highlight the need to situate ethics within historical and geopolitical realities (García Ramírez, 2021;Cañas Quirós, 2023). The ethical question is not merely how to regulate blockchain or ensure transparency in virtual worlds. It is whether digital transformation reproduces one-dimensional rationality-where market logic absorbs ethical discourse-or fosters multidimensional emancipation grounded in material equality.A truly global digital ethics must therefore begin not with code, but with conditions. Without universal connectivity and critical capacity, Web3 and the metaverse risk becoming architectures of selective participation. Ethics, to be universal, must first be infrastructural. Ethics, whether conceived as universal or plural, must first be infrastructural, contextual, and politically grounded.
The rapid collapse of decentralized game economies, often characterized by the \textit{death spiral,} remains the most formidable barrier to the mass adoption of Web3 gaming. This paper proposes that the sustainability of an open game economy is predicated on three necessary and sufficient conditions: Anti-Sybil Resilience, Anti-Capital Dominance, and Anti-Inflationary Saturation. The first section establishes a theoretical proof of these conditions, arguing that the absence of any single dimension leads to systemic failure. The second section explores the dialectical relationship between these dimensions, illustrating how unchecked automation and capital-driven monopolies accelerate asset hyperinflation. In the third section, we introduce the Identity-Bound Asset Integrity Model (IBAIM) as a comprehensive technical solution. IBAIM utilizes Zero-Knowledge (ZK) biometric hashing and Account Abstraction (AA) to anchor asset utility to unique human identities through a privacy-preserving and regulatory-compliant architecture. By exogenizing biometric verification to trusted local environments and utilizing Zero-Knowledge Proofs of Identity (zk-PoI), the model ensures absolute user privacy. Furthermore, by implementing an Asymmetric Utility Decay (AUD) engine-whereby assets suffer a vertical 50% utility cliff upon secondary transfer-and an entropy-driven thermodynamic degradation mechanism., the model successfully decouples financial speculation from in-game merit. Finally, we apply this framework to analyze prominent historical failures in the GameFi sector, demonstrating that their collapse was an inevitable consequence of violating these core economic constraints. Our findings suggest that trading a degree of asset liquidity for system integrity is the only viable path toward long-term economic viability in decentralized virtual worlds.
This study presents a structured dataset of blockchain-registered artificial intelligence agents under the ERC-8004 standard on Ethereum. The dataset integrates on-chain identity records, minting transactions, transfer events, reputation summaries, and individual feedback records, together with resolved off-chain metadata where available. Data were collected from Ethereum mainnet using Web3 RPC queries and processed into tabular form to enable reproducible analysis. The dataset covers 10,000 agents within a defined block range and includes both event-level records and aggregated summaries. It enables empirical research on agent identity formation, reputation systems, service exposure, and early-stage decentralized AI ecosystems. This resource supports studies in blockchain analytics, decentralized trust infrastructure, and the emerging agentic economy.