Neo Rafifing, Alton Mabina, Leatile W. Rafifing
et al.
The rapid development of the Fourth Industrial Revolution is having diverse effects on underdeveloped nations, influencing them in various ways. Developed countries have an advantage over underdeveloped countries since they embraced industrialization earlier, widening the gap between them. This comprehensive survey paper examines the multifaceted landscape of industry 4.0 in supply chain, shedding light on the potential challenges and key value drivers in the context of a developing country. Findings revealed that inadequate digital infrastructure, limited access to electricity, and a shortage of skilled workforce are the primary challenges faced by developing countries in the supply chain domain. The study systematically examines industry 4.0 technologies and indicates a 20-30% improvement in supply chain efficiency through the adoption of key technologies like IoT, AI, and blockchain. The study concludes by offering future research on industry 4.0 in supply chain management. The study results are assumed to offer insightful information to supply chain managers in developing countries, by enabling them with a deeper understanding of the major challenges and key drivers involved in integrating Industry 4.0 in their organizations and network.
Kumar Rahul, Shieh Chin-Shiuh, Chakrabarti Prasun
et al.
Federated Learning (FL) transformed decentralized machine learning by allowing joint model training without mutually sharing raw data, hence being especially useful in privacy-sensitive applications like healthcare, e-commerce, and finance. Even with its privacy-focused architecture, FL is vulnerable to a range of security attacks such as data poisoning, model inversion, membership inference attacks, and communication interception. These attacks compromise the confidentiality of patients in healthcare, consumer data privacy in e-commerce, and financial safety in banking, thus necessitating effective privacy-preserving mechanisms. This survey presents a classification of security threats in FL, grouping them by their source, effect, and attack mode. We review state-of-the-art countermeasures, such as differential privacy, secure multi-party computation, homomorphic encryption, and resilient aggregation methods, their effectiveness, trade-offs, and real-world applicability to FL. In medicine, FL enables joint disease diagnosis without compromising patient confidentiality; in online shopping, it provides personalized suggestions without revealing customer tastes; and in banking, it improves fraud detection without violating regulatory requirements. In addition, we discuss future horizons in privacy-preserving FL, including adversarial robustness, blockchain-protected models, and tailored FL architectures, improving security and resiliency in these domains. We also discuss the balancing problems between security, accuracy, and computational efficiency with possible trade-offs in scaling privacy-preserving FL By analyzing threats and mitigation strategies systematically, this paper will provide direction to future research on designing secure, scalable, and privacy-preserving FL frameworks for the changing healthcare, e-commerce, and finance needs.
IntroductionThis study investigates the integration of financial technology (FinTech) and electronic health (eHealth) to explore the opportunities, challenges, and implications arising from their interlinkage in Saudi Arabia.MethodsUtilizing qualitative semi-structured interviews with 26 participants—including physicians, patients, technical and administrative managers, and FinTech consultants—the research adopts an inductive approach to understand diverse perspectives.ResultsKey findings reveal significant benefits such as improved efficiency in administrative processes, enhanced access to healthcare services, increased financial inclusion, better decision-making, improved patient experience, and the promotion of innovation and sustainability. However, barriers including regulatory challenges, data privacy and security concerns, interoperability issues, the digital divide, resistance to change, and cost implications were also identified.ConclusionOverall, the integration of FinTech and eHealth holds substantial promise for advancing healthcare delivery in Saudi Arabia. Future implications include the expansion of telehealth services, an increase in startups, the integration of wearable health devices, blockchain-based systems, evolving regulatory frameworks, and heightened collaborations. Addressing the identified challenges is crucial for realizing the full potential of this integration.
Jan Kinne, Robert Dehghan, Sebastian Schmidt
et al.
While many digital technologies provide opportunities for creating business models that impact sustainability, some technologies, especially blockchain applications, are often criticized for harming the environment, e.g. due to high energy demand. In our study, we present a novel approach to identifying sustainability-focused blockchain companies and relate their level of engagement to location factors and entrepreneurial ecosystem embeddedness. For this, we use a large-scale web scraping approach to analyze the textual content and hyperlink networks of all US companies from their websites. Our results show that blockchain remains a niche technology, with its use communicated by about 0.6% of US companies. However, the proportion of blockchain companies that are committed to sustainability is significantly higher than in the overall firm population. Additionally, we find that such sustainability-engaged blockchain companies have, at least quantitatively, a more intensive embedding in entrepreneurial ecosystems, while infrastructural and socio-economic location factors hardly play a role.
The concept of the Metaverse, originating from Neal Stephenson’s 1992 novel Snow Crash, has transitioned from a speculative fiction idea into a complex cultural and technological reality. This paper explores the evolution of the Metaverse as both a digital twin of the physical world and a new ‘cultural logic’ permeating various sectors such as gaming, education, and commerce. By integrating immersive technologies such as virtual reality, the Metaverse offers a blended “phygital” environment where users engage in activities ranging from social interactions to commercial transactions, seamlessly merging physical and digital realities. This study delves into how foremost technology leaders have influenced the Metaverse’s trajectory, focusing on transforming it from a gaming interface to a broad digital ecosystem. We analyze the role of blockchain technology in facilitating a network of interconnected spaces that allow for the preservation of digital identities and assets across platforms, highlighting the challenges and potential of achieving interoperability. Ultimately, this paper presents the Metaverse as a paradigm shift in digital interaction, suggesting future directions where digital and physical realities might further converge. Through a comprehensive review of technological advancements and cultural shifts, we discuss the implications of this convergence for future digital interaction frameworks and societal norms.
The construction of new critical infrastructure, represented by high-speed full-time signal coverage, intelligent and fine-grained urban management, and deep space and deep sea scientific innovation experimental fields, has entered a new stage with the deep integration and development of new technologies such as 5G/6G, artificial intelligence, and blockchain in various fields.The security evaluation of cryptography applications, as a key technological resource for ensuring the security of national information, integration, and innovation infrastructure, has risen to the level of international law and national development strategy.It is urgent to construct a comprehensive, fine-grained, and self-evolving cryptography security evaluation system throughout the data lifecycle.The typical APT attacks and ransomware attacks faced by new critical infrastructure in industries such as energy, medicine, and transportation in recent years were considered.And then the growing demand for security evaluation of cryptography applications was analyzed in the face of new business requirements such as preventing endogenous data security risks, achieving differentiated privacy protection, and supporting authenticated attack traceability.The new challenges were also examined, which were brought by new information infrastructure (including big data, 5G communication, fundamental software, etc.), integration infrastructure (including intelligent connected vehicles, intelligent connected industrial control systems, etc.), and innovation infrastructure (including big data, artificial intelligence, blockchain, etc.) to the security evaluation of cryptography applications.Furthermore, the new requirements were revealed about domestically produced cryptography algorithms and protocols deployed on high-performance computing chips, ultra-high-speed communication modules, and large-capacity storage media for cryptography application security evaluation technology.Finally, the development of automated and intelligent cryptography application security evaluation technology was explored.
The primary use of futures is hedging risk. Traders in the spot market can hedge certain risks through the futures market. With the development of the futures market, the arbitrage transactions around futures have attracted increasingly attention. The aim of this paper is to establish an innovative and unique pairs trading framework, and use it to test the effectiveness of China's futures market. The framework for pairs trading is based on cointegration test, Kalman filter and Hurst index filtering. We use the data of 47 commodities with relatively good liquidity in the Chinese commodity futures market. We apply the representative index of China's commodity futures market, ''Wenhua Commodity Index'' as the benchmark, to evaluate the performance of the strategy and compare it with the benchmark model. This study found that, according to the pairs trading framework, after considering transaction costs, the cumulative return in the sample reached 81%, the cumulative return out of the sample was 21%. It is worth noting that the out-of-sample maximum drawdown achieved excellent results of no more than 1%. In the same period, trading the Wenhua Commodity Index with a ''buy and hold'' strategy achieved a gain of 31%, but with maximum drawdown reached 15%. The values of our paper are, first it proves that Chinese commodity futures market is not a weak-form efficient market, because technical analysis based on machine learning could obtain excess returns. Second, this research combines the theory and practice of statistical arbitrage, which also provides guiding significance for investment practice.
History of scholarship and learning. The humanities, Social sciences (General)
Udit Agarwal, Vinay Rishiwal, Sudeep Tanwar
et al.
Supply chain management (SCM) is a core corporate activity responsible for moving commodities and services from one point to another through a variety of stakeholders. The traditional SCM is based on a centralized approach managed at the central headquarter, and all other sub-offices get instructions from the main office. Some major issues with present SCM systems are security, transactional transparency, traceability, stakeholder involvement, product counterfeiting, additional delays, fraud, and instabilities. Blockchain (BC) emerges as a technology that can manage the data and build trust efficiently and transparently. It can also aid in transaction authorization and verification in the supply chain or payments without a third party. To address the present SCM issues, BC technology is a feasible solution. Motivated by the aforementioned considerations, in this paper, we present a survey on the adoption of BC in SCM. This paper undertakes a comprehensive analysis of the literature on BC characteristics, implementations, and business consequences in various SCM. This Blockchain-centered study, in particular, discloses the research state and delineates future research directions by studying and analyzing 97 up-to-date publications highlighting BC’s supply chain uses. Transparency and traceability, information sharing, product anti-counterfeiting, and building trust are the major aspects propelling BC’s implementation in SCM. Further, we analyzed various applications of SCM in which BC can be used as a probable technology to secure all transactions. Then, we have highlighted open issues and research challenges for adopting BC technology in SCM that open the doors for beginners eager to start work in this amazing area.
With the onset of the COVID-19 pandemic and the succession of its waves, the transmission of this disease and the number of deaths caused by it have been increasing. Despite the various vaccines, the COVID-19 virus is still contagious and dangerous for affected people. One of the remedies to this is precaution, and particularly social distancing. In the same vein, this paper proposes a remote voting system, which has to be secure, anonymous, irreversible, accessible, and simple to use. It therefore allows voters to have the possibility to vote for their candidate without having to perform the operation on site. This system will be used for university elections and particularly for student elections. We propose a platform based on a decentralized system. This system will use two blockchains communicating with each other: the public Ethereum blockchain and the private Quorum blockchain. The private blockchain will be institution-specific. All these blockchains send the necessary data to the public blockchain which manages different data related to the universities and the ministry. This system enables using encrypted data with the SHA-256 algorithm to have both security and information security. Motivated by the high energy consumption of blockchain and by the performance improvements in low-power, a test is performed on a low-power embedded platform Raspberry PI4 showing the possibility to use the Blockchain with limited resources.
With the development of the Internet of Things (IoT), the massive data sharing between IoT devices improves the Quality of Service (QoS) and user experience in various IoT applications. However, data sharing may cause serious privacy leakages to data providers. To address this problem, in this study, data sharing is realized through model sharing, based on which a secure data sharing mechanism, called BP2P-FL, is proposed using peer-to-peer federated learning with the privacy protection of data providers. In addition, by introducing the blockchain to the data sharing, every training process is recorded to ensure that data providers offer high-quality data. For further privacy protection, the differential privacy technology is used to disturb the global data sharing model. The experimental results show that BP2P-FL has high accuracy and feasibility in the data sharing of various IoT applications.
FENG Liao-liao, DING Yan, LIU Kun-lin, MA Ke-lin, CHANG Jun-sheng
Since the advent of Bitcoin in 2008, blockchain has gradually become a research hotspot in academia.As the key technology of blockchain, consensus algorithm has also attracted more attention from researchers.It's easy to introduce Byzantine fault nodes in blockchain system because of its complex and variable runtime, so the blockchain Byzantine fault tolerant consensus algorithm is a difficulty that must be overcome.This paper systematically summarizes the research progress of the blockchain Byzantine fault tolerant consensus algorithm, in order to provide a reference for the innovation of consensus algorithms in the future.Firstly, sorting out the four major factions of the existing blockchain Byzantine fault tolerant consensus algorithms and introducing the BFT consensus algorithm.Secondly, reviewing several important values in the classic PBFT algorithm and its correctness proof.Thirdly, putting forward the four optimization goals of the BFT consensus algorithm:decentralization, efficiency, fault tolerance rate and security.Then, based on the dimensions of consensus rounds, number of consensus nodes, underlying hardware, communication mode or encryption algorithm, probability of fault nodes, five optimization ideas of BFT consensus algorithm are summarized.Finally, analysising 10 classic BFT consensus algorithms in detail and making performance comparison.