【Abstract】IT has made significant progress in various fields over the past few years, with many industries transitioning from paper-based to electronic media. However, sharing electronic medical records remains a long-term challenge, particularly when patients are in emergency situations, making it difficult to access and control their medical information. Previous studies have proposed permissioned blockchains with limited participants or mechanisms that allow emergency medical information sharing to pre-designated participants. However, permissioned blockchains require prior participation by medical institutions, and limiting sharing entities restricts the number of potential partners. This means that sharing medical information with local emergency doctors becomes impossible if a patient is unconscious and far away from home, such as when traveling abroad. To tackle this challenge, we propose an emergency access control system for a global electronic medical information system that can be shared using a public blockchain, allowing anyone to participate. Our proposed system assumes that the patient wears a pendant with tamper-proof and biometric authentication capabilities. In the event of unconsciousness, emergency doctors can perform biometrics on behalf of the patient, allowing the family doctor to share health records with the emergency doctor through a secure channel that uses the Diffie-Hellman (DH) key exchange protocol. The pendant's biometric authentication function prevents unauthorized use if it is stolen, and we have tested the blockchain's fee for using the public blockchain, demonstrating that the proposed system is practical.
【Abstract】Smart factories act as focal points to the process of Industry 4.0, and for this reason they pose distinct issues in terms of their applicability within manufacturing organizations. The purpose of this research is to establish the challenges and approaches regarding implementation of smart factories, and it will be based on the manufacturing sector only; results will then be used to analyze and verify for a German firm. The study assesses 47 performance variables placed under nine main groups with the support of the BWM. The application of this approach enables the author to classify the barriers and group them by means of the gathered data and the reference to the other experts' opinions from the case study. Main discoveries highlighted the existence of significant challenges such as connectivity, technology, and program complexity; the need for a flexible software solution; and a stable structure for IT support. New pairs of environmental considerations, such as electronic waste and energy, emerged as important issues, together with ethical issues needed for the safety of society and its employees and the management of information. Implications for theory highlight the necessity of elevating the status of challenges and incorporating applicable factors to improve the appreciation of subjects like e-waste and ethical SCM as priorities. Application-based research suggests conceptual frameworks for smart manufacturing system definition and functioning, with a strong focus on the strategic approach to prioritization and flexibility. Shortcomings are likely to involve the use of consultant advice and the fact that the conclusions are industry-specific. The further study about this subject could be done from a cross-industry perspective, as well as employing integration of new advanced technologies such as blockchain and AI to take the industrial sector to new frontiers of digitalization.
【Abstract】The Industrial Internet of Things (IIoT) promises automation, efficiency, and data-driven decision-making by real-time data collection and analysis. However, traditional IIoT architectures are cloud-centric and, therefore, struggle to handle large volumes of data, edge bandwidth constraints, and data confidentiality. Distributed edge-to-cloud computing emerges as a potential solution, also paving the ground for edge-to-cloud data analytics and distributed Artificial Intelligence (AI) to obtain insights for decision-making and predictive maintenance. Despite the potential, however, there is a lack of comprehensive studies identifying key requirements for distributed edge-to-cloud IIoT and analyzing to what extent emerging IoT platforms meet those requirements. The scope of this article is to survey existing literature to identify key requirements in IIoT from the perspective of distributed edge-to-cloud computing. We provide a comparative analysis of three prominent IoT platforms, namely ThingsBoard, Eclipse Ditto, and Microsoft Azure IoT, and assess how these platforms meet the key IIoT requirements. Finally, we identify open challenges and potential research opportunities based on the insights gained from the analysis of the three IoT platforms, thereby setting the stage for future work.
【Keywords】Industrial Internet of Things; Cloud computing; Scalability; Data analysis; Real-time systems; Distributed databases; Big Data; Industrial Internet of Things (IIoT); edge-to-cloud computing; data analytics; IoT platforms
【Abstract】The agriculture sector stands as one of the most significant sectors sustaining 70 percent of the world's population. In this sector, the supply consists of a series of interconnected stages, spanning from farming through production to the final delivery of goods to the end customer. A lack of transparency within the supply chain presents the largest gap between suppliers and retailers, such as not ensuring the true value of products or services. This research introduces AgroChain, a Blockchain-based system that is designed to support the Agricultural Supply Chain (ASC) process. For scalability purposes, the proposed AgroChain solution comply with a process model that separates the registry of agricultural records from the record itself. The development of the AgroChain prototype along with its smart contracts that establish a transparent, yet secure, environment within the ASC under Quorum which is Ethereum oriented network is illustrated in this research. This research demonstrates that Blockchain networks offer a solution to manage the ASC ensuring traceability, privacy and integrity. Moreover, the research indicates that there is a pressing need to promote the standardization of ASC smart contracts, incorporating secure and straightforward process. Smart contracts have to ideally be implemented in consortium environments, enabling reliable validation of transactions by independent third parties without necessitating access to their content. Moreover, investigating the accountability for illegal activities become challenging.
【摘要】传统教育大数据管理面临隐私数据泄露、数据可信度存疑和越权访问等安全风险,为了避免上述风险,提出了一种新型基于智能合约的教育大数据安全管理与隐私保护算法:ASPES (algorithm for security management and privacy protection of education big data based on smart contracts),算法融合了基于Shamir秘密共享的密钥切割改进分享算法、基于SM2-SHA256-AES算法的混合加密算法和基于分层数据访问控制的智能合约管理算法.在真实数据集MOOCCube上的实验结果表明,相较于较先进的方法,ASPES的执行效率和安全性有显著提高,可以有效存储和管理教育大数据,实现教育资源的合理分配.ASPES通过向区块链中嵌入智能合约,将数据读写等操作上链,能够优化管理路径、提高管理效率,保证教育公平,极大地提升教育质量.
