Decentralized Finance (DeFi) is expected to be the backbone for the metaverse facilitating B2B, B2C, and C2C commerce at scale. Blockchain and smart contracts are key drivers of the DeFi vision, enabling secure and non-repudiable financial transactions based on the fulfillment of pre-defined conditions. However, smart contract business logic can be faulty resulting in erroneous transactions and loss of capital. Testing smart contracts and ensuring 100% correctness also remains a challenge. Finally, to realize the interoperability requirement of the metaverse as mandated by the Metaverse Standards Forum (MSF), service providers shall be required to quickly scale and provide similar services across a plethora of metaverse platforms and ecosystems. Service providers also need to ensure the high availability of their DeFi services and remain resilient in the face of attacks. This research paper presents A Digital Twin Framework for smart contract-based applications for the metaverse, allowing DeFi service providers to create and maintain multiple active and passive twins of their services across metaverse platforms. Passive twins of the service can be used by prospective partners to test their smart contract execution and validate the outcomes. Passive twins can be activated dynamically to improve availability, ensure hyper-scaleup, or respond to attacks. Simulation results establish the effectiveness of the proposed framework laying the foundation for meeting the expectations for the future metaverse.
Valerio Mandarino, Giuseppe Pappalardo, Emiliano Tramontana
Blockchain technology offers unique features, such as transparency, the immutability of data, and the capacity to establish trust without a central authority. Such characteristics can be leveraged to support the collaboration among several different software systems operating within the healthcare ecosystem, while ensuring data integrity and make electronic health records (EHRs) more easily accessible. To provide a solution based on blockchain technology, this paper has evaluated the main issues that arise when large amounts of data are expected, i.e., mainly cost and performance. A balanced approach that maximizes the benefits and mitigates the constraints of the blockchain has been designed. The proposed decentralized application (dApp) architecture employs a hybrid storage strategy that involves storing medical records locally, on users’ devices, while utilizing blockchain to manage an index of these data. The dApp clients facilitate interactions among participants, leveraging a smart contract to enable patients to set authorization policies, thereby ensuring that only designated healthcare providers and authorized entities have access to specific medical records. The blockchain data-immutability property is used to validate data stored externally. This solution significantly reduces the costs related to the utilization of the blockchain, while retaining its advantages, and improves performance, since the majority of data are available off-chain.
Blockchain and artificial intelligence have now become the emerging technologies of our time. However, both strategies induce a change in the market but differ in terms of how creative and complex they are. While block chain is decentralized; distributed ledger technology that the one stores information in multiple locations with no centralized monitoring system, on the other hand, Artificial Intelligence (AI) emulates human problem-solving ability as well as decision-making abilities using software, data or even robots. These two technologies combined together to bring about new opportunities such as productivity gain from both advantages of blockchain and AI security and transparency. Businesses can transform significantly through integration of AI with blockchain technology for data protection, clear data trails and general efficiency. Cyber security is one of the most important concepts linked to these two technologies. The possibility to combine AI’s capabilities with blockchain’s reliable and decentralized nature can be used to manage resources as well as decision making at educational institutes or within healthcare agencies; it may also be employed by society to influence agriculture outputs, planning urban dwellings among others. Artificial intelligence (AI) can help identify risks at an early stage whereas information security and integrity might vanish.
Abdullah J. Abualhamayl, Mohanad A. Almalki, Firas Al-Doghman, Abdulmajeed A. Alyoubi · 5 authors
Abstract In the rapidly evolving digital era, the growing trend of conducting real estate e-business transactions through online platforms has led to escalated challenges in ensuring transactional security and trust. These challenges underscore the importance of balancing transparency with data privacy and enhancing accountability in this field. As an extension of our previously published work (Abualhamayl AJ, Almalki MA, Al-Doghman F, Alyoubi AA, Hussain FK (2023) Towards fractional NFTs for joint ownership and provenance in real estate. In: 2023 IEEE international conference on e-business engineering (ICEBE), p. 143–8. 10.1109/ICEBE59045.2023.00022.), this paper introduces the Global Real Estate Platform (GREP), a novel hybrid blockchain system that utilizes real estate provenance to establish a secure and trustworthy environment for real estate e-business, specifically focusing on two key challenges: ensuring data authenticity and effectively managing access rights. Integral to GREP's design is the involvement of government entities, which is essential for maintaining the required balance between transparency, privacy, and high levels of accountability. This proposed framework is explained conceptually and demonstrated practically, offering an innovative perspective on the integration of hybrid blockchain technology in the real estate system. Furthermore, our research encompasses a detailed implementation, using various tools, and an in-depth examination of three use cases. This combined analysis effectively demonstrates GREP's efficacy in addressing the targeted challenges in the field. While acknowledging the system's limitations, including challenges in user adoption and performance variability under different network conditions, our findings open new avenues for further exploration, such as landlords' payment histories and utility bills, and using blockchain as a secondary user identifier. These features collectively highlight the transformative potential of blockchain technology in real estate e-business.
This paper examines the integration of Blockchain and the Industrial Internet of Things (IIoT) in manufacturing process monitoring. The proposed model emphasizes Blockchain's decentralization, cryptographic security, and smart contracts for enhanced security and efficiency. It addresses challenges like data security and scalability, showcasing the transformative potential of Blockchain-IIoT integration. In the end this work highlights future development opportunities in smart manufacturing.
Data lineage technology is a method of describing the relationships between data, which plays a crucial role in solving many challenges in the data marketplace, such as unauthorized data redistribution, data tampering, and false data transactions. However, the complexity of the multi-chain data marketplace, including factors such as data credibility, trust environment, data ownership, and relationship complexity, poses significant challenges to construct data lineages. To effectively address these challenges, we propose a data lineage construction method for multi-chain data marketplaces. This method mainly involves the following three steps: Firstly, map data assets to Data Non-Fungible Token (DataNFT) and use referable NFT (rNFT) to record data lineage. Secondly, when data assets require cross-chain transfer, the transfer message of DataNFT is broadcasted through the interchain NFT protocol, without the need for actual cross-chain transfer. Finally, we add weights to the data lineage link, enabling us to quickly locate problematic data based on weight sorting during data auditing. We have implemented a system prototype of this method and verified its effectiveness through experiments. The experimental results show that our proposed scheme not only ensures the correctness and completeness of data lineages, but also effectively reduces audit costs.
The rising prominence of blockchain technology has spurred researchers to delve deeper into its applications through the lens of organizational and management theories. Our thematic analysis of blockchain literature reveals examination across five key domains: economic, strategic, operational, behavioral, and implementation considerations, each viewed through various theoretical perspectives. The multifaceted nature of blockchain phenomena necessitates diverse types of theory and research questions. Thus, the unique characteristics within each domain stimulate the formulation of inquiries that address a system of research questions about what, how, why, when, where, what will be, and how to do. Existing literature predominantly emphasizes explanatory and predictive theories, notably expanding research topics such as blockchain adoption behavior. However, this singular focus limits the exploration of diverse reasoning approaches suited to blockchain's complexity. Our study illustrates how different types of theory contribute to understanding each of the identified blockchain application areas. Based on our findings, we propose pertinent questions that highlight the need for varied theoretical frameworks and address specific issues within each application domain. Furthermore, we recommend appropriate theories to address these questions, fostering a more multi-perspective investigation across the breadth of blockchain-related research topics and areas. By embracing diverse theoretical perspectives, we aim to create a more balanced research landscape, facilitating deeper insights into blockchain phenomena.
A. Sasikumar, Logesh Ravi, Malathi Devarajan, V. Subramaniyaswamy · 6 authors
Industry 4.0 requires digital twins (DTs), a potential technology in the transition. By offering current operational statistics visualizations of physical assets, assisting in decision-making, and mitigating possible hazards in electronic manufacturing environments, DTs are essential to the improvement of distributed consumer electronics. DTs must also work with blockchain technology in dispersed consumer electronics systems to anticipate data privacy and access control. Unfortunately, the single failure of DT collaboration is caused by centralized attacks and data interoperability, authentication, scalability, and connectivity issues. This paper provides the secure architecture for the DTs’ collaboration in consumer electronic devices. Next, we have created an access control mechanism based on a consensus model that combines blockchain, digital twin, and real-time monitoring of consumer devices. The proposed framework uses blockchain technology to empower digital twin-based consumer electronic devices. Specifically, we created a collaborative blockchain architecture based on manufacturer, retailer, and device users, emphasizing a distributed chain code model and real-time access control. The experimental results show that the proposed system integration performs better than the baseline digital twin architecture.
Earth observation (EO) data provenance is vital for facilitating data sharing and cooperative processing. However, existing techniques for managing EO data provenance still have various weaknesses, including decentralization, traceability, transparency, tamper-proofing, and security protection. Despite being a transformative solution in various domains, the potential of blockchain technology in EO data provenance remains largely unexplored. This article introduces a blockchain-based solution for EO data provenance, aiming to facilitate data sharing and traceability. We have implemented a prototype based on the blockchain technology and conducted a performance evaluation. To the best of authors' knowledge, this is the first paper to explore the application of blockchain in the management of EO data provenance.
This study investigates cryptocurrency knowledge, risk perception, and investment strategies among İstanbul Provincial Health Directorate employees. Analyzing data from 399 participants using the Cryptocurrency investment Trust Scale, which is developed by Ozyesil and Tembelo (2023), results indicate limited cryptocurrency awareness, moderate risk perception, and conservative investment tendencies. While most participants have heard of cryptocurrency, their understanding remains shalloyv, perceiving it as high-risk and favoring traditional financial instruments. The study emphasizes the necessity of educational initiatives and regulatory frameworks to facilitate safe and compliant cryptocurrency usage within the healthcare sector.
ChainScience 2024, the second edition of the interdisciplinary conference, brought together academics, practitioners, and industry experts to explore novel developments in the realm of distributed ledger technologies. The conference aimed to bridge diverse fields such as informatics, business, economics, finance, regulation, law, mathematics, physics, and complexity science. The papers presented in these conference proceedings address emerging topics such as AI/ML applications to blockchain, DLTs interoperability, decentralized financial services, and tokenomics, alongside ethical, societal, and governance aspects of blockchain and DLTs. With a focus on promoting high-quality research and interdisciplinary collaboration, ChainScience24 aimed to unlock the collective potential of its diverse participants, embodying the ethos that the whole is greater than the sum of its parts.
The Fourth Industrial Revolution (4IR) is transforming education and the way we live and work. To cope with the challenges of 4IR, there is a need for innovative and sustainable teaching and learning tools. AI and blockchain technologies hold great promise in this regard, with potential benefits such as personalized learning, secure credentialing, and decentralized learning networks. This chapter presents a review of existing research on AI and blockchain in education, analyzing case studies and exploring the potential benefits and challenges of these technologies which suggests a unique model for integrating AI and blockchain into sustainable teaching and learning practices. Future research directions are discussed, including the need for more empirical studies and the exploration of ethical and social implications. By enhancing accessibility, efficacy, and security in education, AI and blockchain have the potential to revolutionize the field to ensure that students can benefit from these potentially game-changing technologies as technology develops, it will be crucial to find ways to harness its power while minimizing hazards.
Poonam Rani, Akhtar Hussain, Md. Kaiyum Shaikh, M. Suresh Babu
Research on blockchain technology explores the multifaceted aspects of decentralized and distributed ledger systems. Originating with Bitcoin in 2009, the technology has since evolved beyond cryptocurrencies, gaining prominence in diverse sectors such as finance, supply chain, and healthcare. Scholars have investigated the underlying principles, design considerations, scalability challenges, and potential applications of blockchains. This study aims to map blockchain technology research using bibliometrics and a visualization approach. Scholarly publications on blockchain technology were analyzed using quantitative and qualitative indicators from the Web of Science (WoS) database. A total of 5,249 research articles, spanning a decade (2011-2020) were extracted from the WoS database. This analysis has been enriched using various bibliometric tools, including Biblioshiny, VOSviewer, RStudio, and BibExcel. The key findings of this study revealed that the highest annual growth rate of publications occurred in 2018, with 581 records (184.80%). Author Zhang Y published most of the papers (57) with 1,857 citations. China emerged as the most cited country, with 14,779 world citation shares.
Mallellu Sai Prashanth, V. Uma Maheswari, Rajinikanth Aluvalu, M V V Prasad Kantipudi
INTRODUCTION: Blockchain technology is being investigated as a viable solution due to the industry's growing requirement for accountability and traceability. This study describes a fresh method for tracking down medical products that makes use of a decentralised smart contract network set up on the Ethereum blockchain. In order to enable secure and auditable tracking of health products throughout their lifecycle, the suggested system, named "HealthProductTraceability," makes use of the transparency and immutability of blockchain. OBJECTIVES: The system uses a "Product" struct to hold pertinent data such the product name, batch number, temperature, producer, and distributors. To quickly get product information depending on the batch number, a mapping is used. The use of tools to manufacture items, send them to distributors, and market them is one significant contribution of this research.By demanding validation tests, such as verifying that batch numbers are unique and exist before carrying out certain activities, these functions protect the integrity of the traceability system. METHODS: In order to enable interested parties to track the product's travel and temperature changes, the system additionally emits events for product manufacture, distribution, and temperature adjustments. The suggested system is innovative because it can track the temperature of health items from beginning to end on a decentralised, open platform. RESULTS: By utilising blockchain technology, the system lessens reliance on centralised authorities, fosters stakeholder trust, and minimises the likelihood of fraud, forgery, and tampering in the supply chain for health products. The contract's architecture recognises some of the issues with blockchain technology, including scalability and privacy. By investigating solutions like sidechains, off-chain transactions, and enhancements to consensus methods, scalability issues are solved. CONCLUSION: In summary, the suggested HealthProductTraceability system offers a creative and practical solution to the traceability issues facing the health product sector. The solution provides improved transparency, security, and accountability by utilising blockchain technology, paving the path for a more dependable and trustworthy health product supply chain. To increase the system's usefulness and adoption in real-world circumstances, further research can investigate scalability and privacy issues.
Sura Khalil, Mohammed Hasan Ali, Mustafa Musa Jaber, Ali S. Abosinnee · 8 authors
Business intelligence is becoming more essential for supply chain administrators to make good decisions. The globalization of supply chains makes their management and control more challenging. Blockchain is a distributed digital ledger technology that guarantees traceability, transparency, and security and promises to ease global supply chain management issues. This paper proposes the Blockchain-assisted Secure Data Management Framework (BSDMF) for financial data handling for supply chain integrated business intelligence models. Analyzing, collecting, and demonstrating data could be important to a business, its supply chain performance, and sustainability. The blockchain can interrupt supply chain processes for improved finance handling, distributed management, and process automation. The study’s experimental result will help organizations deploy blockchain applications with intelligent business strategies to support supply chain management effectively. The simulation outcome has been implemented, and the recommended method achieves a computation time of fewer than 2 hours, an efficiency ratio of 97.4%, an error ratio of 94.1%, data authentication of 92.1%, and a data management ratio of 98.7%.
Suelen Bianca de Oliveira Sales, Luciana de Paula Soares
O artigo desenvolve a importância e os desafios enfrentados pela propriedade intelectual no âmbito da nova tecnologia non-fungible token. Conhecido em português como token não fungível, promete revolucionar a forma de se relacionar com a arte a partir de unidades de dados únicas e não fungíveis de itens digitais como imagens, músicas ou vídeos, ou seja, trata-se de algo que é dotado de uma certa “unicidade”. O NFT é criado em Blockchain (tecnologia oriunda da criptomoeda Bitcoin), que garante a transparência e a imutabilidade do ativo digital. Por meio de plataformas próprias focadas em registro de jogos e obras de arte, as pessoas têm a possibilidade de registrar suas criações e comercializá-las dentro destes marketplaces, onde já aconteceram leilões milionários. Promete, ainda, revolucionar a aquisição de bens digitais pela internet e transformar o modo de trabalhar das empresas atualmente. Assim, o trabalho discorre sobre as diversas formas, peculiaridades e aplicabilidades dessa inovação, com foco na segurança jurídica à luz da regulamentação da propriedade intelectual.
Blockchain is a relatively new technology, and its implementation in the life sciences industry is no different. Some of these cases are still in the piloting program stages, but others have already been adopted by life sciences organizations, justifying the emerging need in the field, which is still in its infancy. Blockchain is becoming more important in many different fields and organizations, with a growing influence on pharmaceuticals, biotechnology, and medical device companies. Through this chapter, we will gain a greater understanding of the current applications, future trends, investment areas, and key characteristics of existing life sciences use cases, as well as existing models and platforms of blockchain. About 1524 industry professionals and leaders from relevant functions participated in the survey, 68 which was designed as a global survey. Whether companies already run processes using blockchain technology or not, the chapter examines the impact of these changes on companies with or without blockchain strategies. A study supported by an online survey analyzing the current adoption and application of blockchain will provide key conclusions on how the technology is becoming more prevalent in many life sciences fields despite the challenges it faces. Using the data collected to support the conclusions of this study, the analysis found that a substantial percentage of life sciences leaders and professionals are already aware of blockchain and considering implementing it in the next years. Furthermore, it allowed us to understand that the industry is already comfortable with blockchain, and the mentioned use cases and opportunities gave us very reliable research regarding the most relevant application areas and key considerations for the future. By analyzing the survey results and understanding all the connections and relationships collected from respondents, the interconnectedness between blockchain and the industry is revealed.
Elena Isabel Vazquez Melendez, Paul Bergey, Brett R. Smith
Purpose This study aims to examine the blockchain landscape in supply chain management by drawing insights from academic and industry literature. It identifies the key drivers, categorizes the products involved and highlights the business values achieved by early adopters of blockchain technology within the supply chain domain. Additionally, it explores fingerprinting techniques to establish a robust connection between physical products and the blockchain ledger. Design/methodology/approach The authors combined the interpretive sensemaking systematic literature review to offer insights into how organizations interpreted their business challenges and adopted blockchain technology in their specific supply chain context; content analysis (using Leximancer automated text mining software) for concept mapping visualization, facilitating the identification of key themes, trends and relationships, and qualitative thematic analysis (NVivo) for data organization, coding and enhancing the depth and efficiency of analysis. Findings The findings highlight the transformative potential of blockchain technology and offer valuable insights into its implementation in optimizing supply chain operations. Furthermore, it emphasizes the importance of product provenance information to consumers, with blockchain technology offering certainty and increasing customer loyalty toward brands that prioritize transparency. Research limitations/implications This research has several limitations that should be acknowledged. First, there is a possibility that some relevant investigations may have been missed or omitted, which could impact the findings. In addition, the limited availability of literature on blockchain adoption in supply chains may restrict the scope of the conclusions. The evolving nature of blockchain adoption in supply chains also poses a limitation. As the technology is in its infancy, the authors expect that a rapidly emerging body of literature will provide more extensive evidence-based general conclusions in the future. Another limitation is the lack of information contrasting academic and industry research, which could have provided more balanced insights into the technology’s advancement. The authors attributed this limitation to the narrow collaborations between academia and industry in the field of blockchain for supply chain management. Practical implications Practitioners recognize the potential of blockchain in addressing industry-specific challenges, such as ensuring transparency and data provenance. Understanding the benefits achieved by early adopters can serve as a starting point for companies considering blockchain adoption. Blockchain technology can verify product origin, enable truthful certifications and comply with established standards, reinforcing trust among stakeholders and customers. Thus, implementing blockchain solutions can enhance brand reputation and consumer confidence by ensuring product authenticity and quality. Based on the results, companies can align their strategies and initiatives with their needs and expectations. Social implications In essence, the integration of blockchain technology within supply chain provenance initiatives not only influences economic aspects but also brings substantial social impacts by reinforcing consumer trust, encouraging sustainable and ethical practices, combating product counterfeiting, empowering stakeholders and contributing to a more responsible, transparent and progressive socioeconomic environment. Originality/value This study consolidates current knowledge on blockchain’s capacity and identifies the specific drivers and business values associated with early blockchain adoption in supply chain provenance. Furthermore, it underscores the critical role of product fingerprinting techniques in supporting blockchain for supply chain provenance, facilitating more robust and efficient supply chain operations.
Traditional cloud-centric approaches are facing increasing demands for instant data processing and significant challenges in meeting the latency requirements of modern applications. Edge computing emerges as a promising approach that brings computation and data storage closer to the edge of the network, enabling real-time decision-making with reduced latency and enhanced efficiency. The paper provides a comprehensive overview of edge computing, describing its fundamental principles, architectural components, and key advantages over centralized cloud infrastructures. By minimizing data transfer latency, edge computing ensures that critical data analysis and processing occur close to data sources, resulting in enhanced responsiveness and improved user experiences. The paper analyzes two case studies, including autonomous driving vehicles and finance, in order to highlight the applications of edge computing in areas where real-time decision-making is crucial. In addition to discussing the benefits of edge computing, the paper addresses the potential challenges and constraints associated with edge computing implementation. Security and privacy concerns in decentralized edge environments are explored, and several protection strategies are described. Finally, the paper outlines the future of edge computing for organizations and the technology industry. In doing so, the paper discusses the potential of edge computing in supporting emerging technologies, such as 5G networks and autonomous systems. Received: December 19, 2023Accepted: February 2, 2024
Wang Jun, Muhammad Shahid Iqbal, Rashid Abbasi, Marwan Omar · 5 authors
Machine learning is playing an increasingly important role in education. This article examines its potential to bring about transformative change in this field. By using machine learning algorithms, physical education teachers can gather and analyze data on student performance and behavior. This enables them to create personalized learning experiences that cater to the unique needs of each student. Machine learning can also track and assess student progress, providing educators with valuable insights into the effectiveness of their teaching strategies. Furthermore, it can optimize the design of physical education curricula and assessments, making them more efficient and effective. Additionally, machine learning offers a more objective and accurate approach to evaluating and grading students. This paper discusses the challenges and opportunities associated with integrating machine learning into physical education, including ethical considerations and potential limitations.
Mifta Ahmed Umer, Elefelious Getachew Belay, Luís Borges Gouveia
Cloud manufacturing is an evolving networked framework that enables multiple manufacturers to collaborate in providing a range of services, including design, development, production, and post-sales support. The framework operates on an integrated platform encompassing a range of Industry 4.0 technologies, such as Industrial Internet of Things (IIoT) devices, cloud computing, Internet communication, big data analytics, artificial intelligence, and blockchains. The connectivity of industrial equipment and robots to the Internet opens cloud manufacturing to the massive attack risk of cybersecurity and cyber crime threats caused by external and internal attackers. The impacts can be severe because the physical infrastructure of industries is at stake. One potential method to deter such attacks involves utilizing blockchain and artificial intelligence to track the provenance of IIoT devices. This research explores a practical approach to achieve this by gathering provenance data associated with operational constraints defined in smart contracts and identifying deviations from these constraints through predictive auditing using artificial intelligence. A software architecture comprising IIoT communications to machine learning for comparing the latest data with predictive auditing outcomes and logging appropriate risks was designed, developed, and tested. The state changes in the smart ledger of smart contracts were linked with the risks so that the blockchain peers can detect high deviations and take actions in a timely manner. The research defined the constraints related to physical boundaries and weightlifting limits allocated to three forklifts and showcased the mechanisms of detecting risks of breaking these constraints with the help of artificial intelligence. It also demonstrated state change rejections by blockchains at medium and high-risk levels. This study followed software development in Java 8 using JDK 8, CORDA blockchain framework, and Weka package for random forest machine learning. As a result of this, the model, along with its design and implementation, has the potential to enhance efficiency and productivity, foster greater trust and transparency in the manufacturing process, boost risk management, strengthen cybersecurity, and advance sustainability efforts.
Alven C. Y. Leung, Dennis Liu, Xiapu Luo, Man Ho Au
Abstract Blockchain is a newly emerging technology in the past decade that has significantly impacted various aspects. “Scientific popularization” among IT practitioners on this technology and its use cases become a pressing need. However, constructing an effective blockchain teaching approach for this purpose is a challenging task. A training framework consisting of constructivist and pragmatic approaches is proposed, aiming to provide IT practitioners with an effective Teaching and Learning (T &L) process about blockchain on both theory and application aspects. The outcomes of this study are to 1) propose an effective teaching methodology, 2) assess the effectiveness of constructivist and pragmatic approaches and 3) extract the elements facilitating blockchain T &L. Mixed quantitative and qualitative research methods were adopted, including questionnaires and knowledge quizzes. 1267 participants were involved in the training that implemented the proposed framework. Their performance and responses indicated that the framework is effective and flexible. The findings from this empirical research can serve as a reference for educators in blockchain to implement a systemic approach that facilitates the T &L process and improves the field of blockchain and education in the future.