Cryptocurrencies and Web3 applications based on blockchain technology have flourished in the blockchain research field. Unlike Bitcoin and Ethereum, due to its unique architectural designs in consensus mechanisms, resource management, and throughput, TRON has developed a more distinctive ecosystem and application scenarios centered around stablecoins. Although it is popular in areas like stablecoin payments and settlement, research on analyzing on-chain data from the TRON blockchain is remarkably scarce. To fill this gap, this paper proposes a comprehensive data extraction and exploration framework for the TRON blockchain. An innovative high-performance ETL system aims to efficiently extract raw on-chain data from TRON, including blocks, transactions, smart contracts, and receipts, establishing a research dataset. An in-depth analysis of the extracted dataset reveals insights into TRON's block generation, transaction trends, the dominance of exchanges, the resource delegation market, smart contract usage patterns, and the central role of the USDT stablecoin. The prominence of gambling applications and potential illicit activities related to USDT is emphasized. The paper discusses opportunities for future research leveraging this dataset, including analysis of delegate services, gambling scenarios, stablecoin activities, and illicit transaction detection. These contributions enhance blockchain data management capabilities and understanding of the rapidly evolving TRON ecosystem.
This paper proposes a hybrid access control system that integrates the usability of Web2 authentication (Google Login) with the transparency and integrity of Web3 technologies (blockchain and smart contracts). The system enables users to authenticate via their existing Google accounts without managing crypto wallets or private keys, while access permissions are securely recorded on-chain through smart contracts. To ensure cryptographic key security without relying on a centralized authority, the design incorporates Distributed Key Management (DKM). This approach addresses the challenge of balancing usability with verifiability in data access control. By embedding decentralized guarantees within a centralized web service interface, the system enables practical and transparent access control. The proposed architecture demonstrates the potential for a general-purpose, auditable module that facilitates user-consented data sharing with third parties.
Escrow trust is a foundational requirement for high-value campaign execution in Web3 marketing marketplaces. When campaign budgets exceed USD 50,000 and settlement is enforced on-chain, the security properties of the escrow contract and its surrounding settlement architecture determine whether the platform can be trusted by enterprise brands. Naive escrow designs — single-key deployment, monolithic contract logic, and implicit state transitions — expose platforms to fund loss through key compromise, smart contract exploit, and fraudulent dispute resolution. This paper presents SESA (Secure Escrow and Settlement Architecture), a formal engineering framework for Web3 campaign escrow that integrates multi-signature approval policies, strict role segregation between campaign management and fund release authority, control-plane and data-plane separation with hardware-backed signing, and explicit finite-state machine governance of all escrow lifecycle transitions including dispute resolution. SESA is grounded in a formal threat model that enumerates eleven attack vectors specific to Web3 escrow systems and maps each to a corresponding architectural control. A formal verification of the escrow state machine using the TLA+ specification language demonstrates the absence of deadlock, fund loss, and unauthorised release under all reachable states. A gas cost analysis of the reference Solidity implementation demonstrates that SESA's security controls add a mean overhead of 23% in gas cost relative to a naive single-key escrow — a trade-off that enterprise buyers consistently accept in exchange for verifiable security assurances. SESA enables campaign budgets that would be commercially unviable under insecure escrow designs to flow safely through the platform, directly expanding the addressable market for high-value brand partnerships.
Blockchain technology has emerged as a transformative force across a multitude of sectors, offering decentralized, transparent, and tamper-proof solutions to conventional problems in data management, finance, supply chain, healthcare, and beyond.Initially popularized through cryptocurrencies, blockchain has since evolved into a broader infrastructure supporting smart contracts, decentralized applications (dApps), and Web3 ecosystems.This survey provides a comprehensive overview of blockchain technology, outlining its fundamental principles including distributed ledgers, consensus mechanisms, cryptographic security, and decentralization.We critically examine various blockchain architectures such as public, private, and consortium blockchains, and explore their relative strengths and limitations.The paper further delves into current trends, emerging use cases, scalability challenges, interoperability issues, and security concerns.By synthesizing recent academic and industry developments, this survey aims to provide researchers and practitioners with a holistic understanding of blockchain's capabilities, current limitations, and future directions.
Web3 applications require execution platforms that maintain confidentiality and integrity without relying on centralized trust authorities. While Trusted Execution Environments (TEEs) offer promising capabilities for confidential computing, current implementations face significant limitations when applied to Web3 contexts, particularly in security reliability, censorship resistance, and vendor independence. This paper presents dstack, a comprehensive framework that transforms raw TEE technology into a true Zero Trust platform. We introduce three key innovations: (1) Portable Confidential Containers that enable seamless workload migration across heterogeneous TEE environments while maintaining security guarantees, (2) Decentralized Code Management that leverages smart contracts for transparent governance of TEE applications, and (3) Verifiable Domain Management that ensures secure and verifiable application identity without centralized authorities. These innovations are implemented through three core components: dstack-OS, dstack-KMS, and dstack-Gateway. Together, they demonstrate how to achieve both the performance advantages of VM-level TEE solutions and the trustless guarantees required by Web3 applications. Our evaluation shows that dstack provides comprehensive security guarantees while maintaining practical usability for real-world applications.
Muhammad Haroon Tariq, Uswa Ihsan, Zaenal Alamsyah
Ownership rights related to land and property represent a highly contentious matter in areas across Pakistan because female inheritors struggle to assert their property rights due to cultural practices along with unclear procedures and traditional document systems. The present government-controlled systems demonstrate inadequate proficiency along with safety protocols to execute fair inheritance distribution, mainly impacting marginalized populations. This research introduces a blockchain system known as the Land Registration and Inheritance Automation System (LRIAS) which prioritizes the female protection of inheritance privileges. The proposed system includes digitalizing the traditional paper-based land registration and inheritance process. The system ensures blockchain security through the implementation of MetaMask together with Web3.js for Ethereum transactions. The blockchain system distributes inheritances through programmed agreements which follow Shariah validation rules. The LRIAS establishes permanent and free-version records that show who owns land and who the legal heirs are. The system enables women to access their inheritance records through verifiable reliable data which cannot be altered. Through the system, authorities can verify inheritance claims and execute them without bureaucratic interference, which minimizes both legal disputes and family conflicts. Experimental tests show that the LRIAS succeeds in safeguarding women’s land inheritance claims and increasing confidence in legal inheritance procedures.
This study discusses the behavior of decentralized decision-making of investment in Web3 environment, and the primary factors affecting the decision of investors, including governance with transparence and fair process, opinion of the community, fluctuations of markets, and trends of social networks. From DeFi platforms and markets of NFT, this study finds the inclination of investors towards governance with transparence and fair process when selecting projects, and decisive impacts of opinion of the community on decision. This study also finds significant impacts of social network and fluctuations of markets on short-term investment, and greater risk appetite of investors under more fluctuations of markets. This study verifies the impacts of these factors on the Web3 environment of investment with data simulation under a virtual environment, provides in-depth understanding of behavior of investment under decentralized finance and markets of NFT, and provides valuable references for related projects' design and operation.
Abstract This article focuses on the Network State movement as embodying the venture capital (VC) logic of exit. Exit constitutes both a strategy for lucrative returns and an ideology seeking out new territories for financial and technological speculation. This movement has emerged around Balaji Srinivasan and the technologies of Web3 that encode the imperatives of exit. In the construction of liberated zones for the Network State, VC operates through a territorial logic, under the leadership of the founder‐philosopher and with the affordances of the American state. These logics evince the discursive power at the heart of the political economy of VC. The desires of the VC class shape “future social necessity” (Howard 2024; Finance and Society 10) and are “imprinted” (Cooiman 2024; Environment and Planning A 56) upon the social and technological networks of the Network State. The valorisation through exit seeks to produce “hyperstitious” (Lynch and Muñoz‐Viso 2023; Progress in Human Geography 48) value creation in which VC is the fount of civilisation.
Ovaj rad predstavlja razvoj prototipa decentralizirane društvene mreže temeljene na tehnologijama Web3. S obzirom na sve veće nepovjerenje korisnika prema tradicionalnim, centraliziranim društvenim mrežama, cilj je izraditi rješenje koje korisnicima omogućuje privatnost, sigurnost i vlasništvo nad vlastitim podacima. Aplikacija koristi blockchain Ethereum za upravljanje identitetom i interakcijama korisnika i Metamask za autentikaciju. Sadržaj se pohranjuje distribuirano putem sustava IPFS i mreže istorazinskih dionika Gun. Implementirane su funkcionalnosti poput objavljivanja sadržaja, spremanje objava, označavanje objava sa "sviđa mi se", komentiranja, slanja zahtjeva za prijateljstvo i drugih interakcija. Uz sve navedeno, aplikacija uključuje izravni (peer-to-peer) chat, te sustav za nagrađivanje korisnika putem ERC-20 tokena za aktivnosti, interakciju i kvalitetan sadržaj. Sustav je implementiran lokalno pomoću IPFS i GUN čvorova na dva uređaja. Postavljen je temelj za daljnju optimizaciju i širenje funkcionalnosti, kako bi se ostvarila stvarna, sigurna i decentralizirana mreža.
Nicolò Romandini, Carlo Mazzocca, Kai Otsuki, Rebecca Montanari
Blockchain and smart contracts have garnered significant interest in recent years as the foundation of a decentralized, trustless digital ecosystem, thereby eliminating the need for traditional centralized authorities. Despite their central role in powering Web3, their complexity still presents significant barriers for non-expert users. To bridge this gap, Artificial Intelligence (AI)-based agents have emerged as valuable tools for interacting with blockchain environments, supporting a range of tasks, from analyzing on-chain data and optimizing transaction strategies to detecting vulnerabilities within smart contracts. While interest in applying AI to blockchain is growing, the literature still lacks a comprehensive survey that focuses specifically on the intersection with AI agents. Most of the related work only provides general considerations, without focusing on any specific domain. This paper addresses this gap by presenting the first Systematization of Knowledge dedicated to AI-driven systems for blockchain, with a special focus on their security and privacy dimensions, shedding light on their applications, limitations, and future research directions.
The InterPlanetary File System (IPFS) has been successfully established as the de facto standard for decentralized data storage in the emerging Web3. Despite its decentralized nature, IPFS nodes, as well as IPFS content providers, have converged to centralization in large public clouds. Centralization introduces BGP routing-based attacks, such as passive interception and BGP hijacking, as potential threats. Although this attack vector has been investigated for many other Web3 protocols, such as Bitcoin and Ethereum, to the best of our knowledge, it has not been analyzed for the IPFS network. In our work, we bridge this gap and demonstrate that BGP routing attacks can be effectively leveraged to censor content in IPFS. For the analysis, we collected 3,000 content blocks called CIDs and conducted a simulation of BGP hijacking and passive interception against them. We find that a single malicious AS can censor 75% of the IPFS content for more than 57% of all requester nodes. Furthermore, we show that even with a small set of only 62 hijacked prefixes, 70% of the full attack effectiveness can already be reached. We further propose and validate countermeasures based on global collaborative content replication among all nodes in the IPFS network, together with additional robust backup content provider nodes that are well-hardened against BGP hijacking. We hope this work raises awareness about the threat BGP routing-based attacks pose to IPFS and triggers further efforts to harden the live IPFS network against them.
Mohamad Sheikho Al Jasem, Trevor De Clark, Ajay Kumar Shrestha
The convergence of decentralized artificial intelligence (DAI), blockchain technology, and smart contracts is reshaping the design and governance of intelligent systems. As these technologies rapidly evolve, addressing privacy within their architecture, usage models, and associated risks has become increasingly critical. This systematic literature review examines architectural patterns, governance frameworks, real-world applications, and persistent challenges in DAI systems. It identifies prevailing designs such as federated learning integrated with consensus protocols, smart contract-based incentive mechanisms, and decentralized verification methods. Drawing from a diverse body of recent literature, the review highlights implementations across sectors, including healthcare, finance, IoT, autonomous systems, and intelligent infrastructure, each demonstrating significant contributions to privacy, security, and collaborative innovation. Despite these advancements, DAI systems face ongoing obstacles such as scalability limitations, privacy trade-offs, and difficulties with regulatory compliance. The review emphasizes the need for integrative governance approaches that balance transparency, accountability, incentive alignment, and ethical oversight. These elements are proposed as co-evolving pillars essential to establishing trustworthiness in decentralized AI ecosystems. This work offers a comprehensive review for understanding the current landscape and guiding the development of responsible and effective DAI systems in the Web3 era.
Andrea Michienzi, Laura Pollacci, Barbara Guidi, Francesco Maggio
Nowadays, Social Media represents an important window to address societal issues and promote social causes. However, Social Media suffer from several issues concerning fake news, misinformation, disinformation, etc. To address these issues, decentralization has been proposed to overcome current limitations. Blockchain-based Online Social Media (BOSM) offer verifiable platforms, usually enriched with reward systems that allow users to get paid according to the social value they create. Reward systems can economically empower creators and other individuals beyond high-quality content, allowing content creators to earn income. Considering the widespread use of BOSM platforms and various incentive methods, tools are needed to analyze and guide these rewarding strategies to avoid the risk of speculative mechanisms. In this paper, we propose BISON, a predictive and interpretable framework for identifying the drivers of success in blockchain-native articles. BISON can model success not as a purely financial outcome, but as a composite function of content attributes and user engagement patterns, as recorded on the blockchain. Its modular architecture allows for empirical validation across multiple datasets and makes it adaptable to other Web3 platforms. Additionally, our framework introduces Explainable AI into the blockchain content domain.
The unprecedented rise of Bitcoin has marked a significant milestone in the evolution of decentralized finance (DeFi). Despite Bitcoin's groundbreaking contributions, it faces inherent challenges due to its reliance on the Unspent Transaction Output (UTXO) model, which limits its capabilities in executing complex transactions and embedding diverse data types. To overcome these limitations, Ordinals and Inscriptions have been introduced, allowing extensive data and information embedding within Bitcoin transactions. Building upon these advancements, the recent development of the BRC-20 standard leverages these capabilities to introduce fungible tokens on the Bitcoin network. However, these innovations have yet to be fully integrated into the broader blockchain and DeFi ecosystems, and they still face challenges related to interoperability, scalability, and user perception. In this paper, we explore the intricacies of Ordinal, Inscription, and BRC protocols to address these challenges by analyzing their functionalities, operational methodologies, and potential applications. We offer a detailed examination of the challenges and future prospects, shedding light on the unexplored potential of these technologies in transforming Bitcoin transactions and expanding its role in the DeFi space. By thoroughly analyzing these new developments, we aim to bridge the gap in current academic research and offer valuable insights for developers, investors, and enthusiasts. This paper serves as a foundation for future innovations, paving the way for more robust, scalable, and user-friendly applications in the DeFi and Web3 landscape.
The article explores the evolution of marketing innovations in the retail sector through the lens of technological development and the transformation of consumer expectations. Five key stages of innovation development are identified—traditional, network based, digital, omnichannel, and innovation-technological—each characterized by specific challenges, opportunities, and influencing factors. The traditional stage was marked by a focus on product policy and individual promotions within the physical store. The network-based stage introduced the integration of IT solutions into logistics, CRM systems, and initial customer segmentation. The digital stage was distinguished by the emergence of online stores, mobile marketing, and personalized communication. The omnichannel stage involved the full synchronization of online and offline channels to ensure a holistic customer experience. The innovation-technological stage includes the extensive implementation of artificial intelligence, AR/VR, blockchain, and emotional analytics. The study draws conclusions about the patterns of transition between stages and the role of innovation in transforming business models in retail. Key directions for further development of marketing innovations are identified, including the technologization of customer experience, intelligent marketing automation, a sustainable approach, Web3 integration, the growth of social commerce, and the use of emotional analytics. However, the implementation of these directions is accompanied by a number of challenges related to the rapid pace of technological change, increasing consumer expectations, and the need to adapt business models to new ethical and environmental standards. In Ukraine, these challenges are further intensified by martial law conditions, market instability, limited resources, and the urgent need for rapid transformation of the retail sector to fit the new realities. It is noted that the development vectors of marketing innovations in retail form a complex yet high-potential system of change that requires strategic thinking, flexibility, and readiness to implement new formats of customer interaction. The article has practical significance for marketing professionals, retail business managers, and researchers working on adapting business practices to the evolving digital economy.
In the rapidly evolving landscape of digital marketing and electronic commerce, short-form content—particularly on platforms like Twitter (now X)—has become pivotal for real-time branding, community engagement, and product promotion. The rise of Non-Fungible Tokens (NFTs) and Web3 ecosystems further underscores the need for domain-specific, engagement-oriented social media content. However, automating the generation of such content while balancing linguistic quality, semantic relevance, and audience engagement remains a substantial challenge. To address this, we propose RL-TweetGen, a socio-technical framework that integrates instruction-tuned large language models (LLMs) with reinforcement learning (RL) to generate concise, impactful, and engagement-optimized tweets. The framework incorporates a structured pipeline comprising domain-specific data curation, semantic classification, and intent-aware prompt engineering, and leverages Parameter-Efficient Fine-Tuning (PEFT) with LoRA for scalable model adaptation. We fine-tuned and evaluated three LLMs—LLaMA-3.1-8B, Mistral-7B Instruct, and DeepSeek 7B Chat—guided by a hybrid reward function that blends XGBoost-predicted engagement scores with expert-in-the-loop feedback. To enhance lexical diversity and contextual alignment, we implemented advanced decoding strategies, including Tailored Beam Search, Enhanced Top-p Sampling, and Contextual Temperature Scaling. A case study focused on NFT-related tweet generation demonstrated the practical effectiveness of RL-TweetGen. Experimental results showed that Mistral-7B achieved the highest lexical fluency (BLEU: 0.2285), LLaMA-3.1 exhibited superior semantic precision (BERT-F1: 0.8155), while DeepSeek 7B provided balanced performance. Overall, RL-TweetGen presents a scalable and adaptive solution for marketers, content strategists, and Web3 platforms seeking to automate and optimize social media engagement. The framework advances the role of generative AI in digital commerce by aligning content generation with platform dynamics, user preferences, and marketing goals.
<b>Abstract</b><br>Traditional electoral systems exhibit critical vulnerabilities including vote manipulation, centralized points of failure, and compromised transparency that undermine democratic integrity. This research presents BLOCKELECT, a decentralised blockchain-based secure voting system designed to address these fundamental challenges. The system employs Ethereum smart contracts written in Solidity to enforce immutable voting rules, Web3.js for blockchain integration, and MetaMask wallet authentication for secure voter verification. The proposed architecture implements dual interfaces for voters and electoral commissions, with distributed consensus mechanisms ensuring real-time transaction validation. Smart contracts automatically enforce electoral rules while maintaining cryptographic immutability of all voting transactions. The decentralised design eliminates single points of failure by distributing vote storage and validation across multiple network nodes. System validation employed comprehensive testing including unit, integration, system, and security testing methodologies. Results demonstrate successful prevention of vote tampering, elimination of double voting, and provision of transparent, auditable election results. Implementation utilised Truffle framework, Ganache blockchain simulation, and Node.js back-end services following an Agile Prototype-based Iterative Development methodology. This research demonstrates the feasibility of blockchain technology in creating trustworthy electoral systems, indicating that blockchain-based voting represents a viable solution for enhancing democratic processes while addressing persistent challenges of electoral fraud and lack of public confidence in traditional voting mechanisms.Traditional electoral systems exhibit critical vulnerabilities including vote manipulation, centralized points of failure, and compromised transparency that undermine democratic integrity. This research presents BLOCKELECT, a decentralised blockchain-based secure voting system designed to address these fundamental challenges. The system employs Ethereum smart contracts written in Solidity to enforce immutable voting rules, Web3.js for blockchain integration, and MetaMask wallet authentication for secure voter verification. The proposed architecture implements dual interfaces for voters and electoral commissions, with distributed consensus mechanisms ensuring real-time transaction validation. Smart contracts automatically enforce electoral rules while maintaining cryptographic immutability of all voting transactions. The decentralised design eliminates single points of failure by distributing vote storage and validation across multiple network nodes. System validation employed comprehensive testing including unit, integration, system, and security testing methodologies. Results demonstrate successful prevention of vote tampering, elimination of double voting, and provision of transparent, auditable election results. Implementation utilised Truffle framework, Ganache blockchain simulation, and Node.js back-end services following an Agile Prototype-based Iterative Development methodology. This research demonstrates the feasibility of blockchain technology in creating trustworthy electoral systems, indicating that blockchain-based voting represents a viable solution for enhancing democratic processes while addressing persistent challenges of electoral fraud and lack of public confidence in traditional voting mechanisms.
"With growing concerns about mental well-being, users want efficacious means to monitor emotions and get personalized assistance, with current solutions often sacrificing privacy or offering shallow revelations. ZenLoop overcomes the shortcomings by combining AI-based analysis of emotion with safe Web3 storage to provide both well-being support alongside privacy. This paper builds a conversational AI chatbot that offers coping mechanisms, a mood tracker to record emotion states, and an analysis dashboard to enable users to identify behavior patterns. Developed with React for frontend, Node.js for backend, and MongoDB for organized data, ZenLoop provides empathy-based responses leveraging NLP models trained on mental well-being dialogues. Journals are encrypted and stored in Web3-based storage, with immutable, decentralized protection. Trends in moods are depicted in interactive graphs, and AI-driven insights enable users to monitor emotion shifts. Tests show enhanced user engagement, improved self-perception, along with superior protection of data. The chatbot is effective in detecting levels of distress along with recommended interventions, promoting emotional resilience. By combining AI-driven tools for mental well-being with the security of blockchain, ZenLoop enables users to express emotion securely, monitor their mental well-being patterns, and get personalized advice at no cost of privacy. This work demonstrates the potential of privacy-based AI-based solutions to promote well-being at the emotional level, leading to the development of secure, user-centric applications for mental well-being.
By Elizabeth Enkin, University of Nebraska-Lincoln DOI: https://www.doi.org/10.69732/CKTL9913 As language teachers, we are keenly aware of the important benefits that Web 2.0, the collaborative web, has brought to language teaching. From social media to audio and visual tools, Web 2.0
This article explores how the integration of Artificial Intelligence (AI), Machine Learning (ML), Web3.0, Blockchain, Metaverse, and Non-Fungible Tokens (NFTs) will revolutionize various aspects of public life globally over the next decade. We introduce novel perspectives such as AI-driven decentralized governance, blockchain-based universal basic income, and metaverse-enabled global education platforms. These technologies will transform global supply chains through AI-driven forecasting and blockchain-verified logistics, ensuring transparency and efficiency. Healthcare will advance with AI-powered telemedicine and personalized treatments, reducing disparities in underserved regions. Autonomous systems will enhance urban mobility and disaster response, fostering sustainable smart cities. Web3.0 will empower users with decentralized digital identities and data sovereignty, redefining advertising and social media through token-based models. Blockchain will secure academic credentials, streamline insurance, and enable transparent philanthropy, while carbon credit markets promote sustainability. The metaverse will revolutionize remote work, healthcare consultations, and cultural preservation through immersive virtual environments. NFTs will democratize real estate and creative economies, enabling tokenized ownership and secure voting systems. Synergistically, these technologies will create decentralized e-commerce, disaster response systems, and virtual innovation hubs, fostering equitable digital ecosystems. However, challenges like digital divides, AI biases, and blockchain scalability must be addressed to ensure inclusive adoption. This article envisions a future where these advancements redefine governance, economies, and social interactions, paving the way for an innovative, equitable global society. AI-driven avatars and decentralized AI training platforms will further enhance virtual collaboration, while tokenized cultural assets empower communities, ensuring a resilient, inclusive digital future.
The rapid development of large language models (LLMs) has significantly propelled the development of artificial intelligence (AI) agents, which are increasingly evolving into diverse autonomous entities, advancing the LLM-based multi-agent systems (LaMAS). However, current agentic ecosystems remain fragmented and closed. Establishing an interconnected and scalable paradigm for Agentic AI has become a critical prerequisite. Although Agentic Web proposes an open architecture to break the ecosystem barriers, its implementation still faces core challenges such as privacy protection, data management, and value measurement. Existing centralized or semi-centralized paradigms suffer from inherent limitations, making them inadequate for supporting large-scale, heterogeneous, and cross-domain autonomous interactions. To address these challenges, this paper introduces the blockchain-enabled trustworthy Agentic Web (BetaWeb). By leveraging the inherent strengths of blockchain, BetaWeb not only offers a trustworthy and scalable infrastructure for LaMAS but also has the potential to advance the Web paradigm from Web3 (centered on data ownership) towards Web3.5, which emphasizes ownership of agent capabilities and the monetization of intelligence. Beyond a systematic examination of the BetaWeb framework, this paper presents a five-stage evolutionary roadmap, outlining the path of LaMAS from passive execution to advanced collaboration and autonomous governance. We also conduct a comparative analysis of existing products and discuss key challenges of BetaWeb from multiple perspectives. Ultimately, we argue that deep integration between blockchain and LaMAS can lay the foundation for a resilient, trustworthy, and sustainably incentivized digital ecosystem. A summary of the enabling technologies for each stage is available at https://github.com/MatZaharia/BetaWeb.
Breno Jacinto Duarte da Costa, Márcio Ferro, Mohamed Yassine Zarouk, Alan Silva · 6 authors
Education 4.0 promotes active, personalized, and competency-based learning aligned with the Sustainable Development Goals (SDGs), yet most current platforms rely on centralized architectures that restrict access, agency, and adaptability. To address this problem, Web3 technologies—including blockchain, decentralized identifiers (DIDs), peer-to-peer storage, and smart contracts—enable the creation of platforms that uphold equity, data sovereignty, and pedagogical flexibility. This paper investigates how the convergence of Education 4.0 and Web3 technologies can drive the development of sustainable, inclusive, and learner-centered digital education systems. We examine two decentralized education platforms, EtherLearn and DeLMS, to assess their design affordances and limitations. Building on these insights, we propose a layered architectural framework grounded in sustainability principles. Our analysis shows that decentralized infrastructures can expand access in underserved regions, increase credential portability, empower learners with greater autonomy, and foster participatory governance through decentralized voting, token-based incentives, and community moderation. Despite these advantages, significant challenges remain around usability, energy efficiency, and regulatory compliance. We conclude by identifying key research priorities at the intersection of sustainable educational technology, digital equity, and decentralized system design.
Abdul Razzaq, Ahmed B. Altamimi, Wilayat Khan, Mohammad Alsaffar · 7 authors
CONTEXT: Metaverse is an emerging technology that synchronizes physical and virtual things. It is used to communicate and simulate the virtual world with the physical world through human actions in real-life scenarios. Combining blockchain and metaverse technologies produces an archetype shift in the educational technology domain regarding online certification, largely due to the impact of synchronizing educational technologies. The combined technology elevates the security measure, ensures transparency, enhances accountability, and reduces costs for the online certification process. Proposed Solution: The suggested solution (MetaEduTech) accelerates the certificate verification process by (i) extenuating the risks of misuse by leveraging decentralized storage of the InterPlanetary File System (IPFS), (ii) securing the certificate, and (iii) providing the metaverse environment for certification. We perform experiments and evaluate the MetaEduTech solution by deploying a blockchain-based smart contract model on Ethereum on the Microsoft Windows platform. RESULTS AND IMPLICATIONS: The evaluation results show (i) the efficiency of the query response (5 ms-50 ms), (ii) and the performance of the query execution (CPU utilization between 2%-6%). The findings in this research underscore the effectiveness of the proposed solution with the potential to modernize the certification exam process. The proposed solution and its evaluation can provide insights into how to address the persistent issues surrounding certificate authenticity related to academic verification in a metaverse environment.