【Abstract】Aiming at the problems of information storage security and information sharing among various medical infor-mation systems, combined with blockchain consensus mechanism, encryption mechanism, peer-to-peer network, and other technologies. A medical information system scheme based on blockchain is proposed to realize the storage and sharing of medical information. The program has the characteristics of non-tampering and decen-tralization. This paper has designed a Practical Byzantine fault tolerance (PBFT) medical blockchain information management system. This system is multi-node maintenance and shared management system that can prevent medical information data from being tampered with and medical information leakage. It can be used to solve Medical information data management problems. Compared with the existing medical blockchain system, this medical information management system has certain advantages and better applicability.
【Abstract】Renewable Energy (RE) decentralisation has become a means towards energy sustainability due to the revolution in blockchain technology. RE sources have undergone remarkable growth as a result of the privatisation of the energy industry and the boost in incentives and policy initiatives on energy. As supply and demand are affected by a sudden change in weather conditions, a new set of challenges in how electricity systems are managed and operated have emerged. Therefore, a level of flexibility measures for safety and stability is required. Blockchain as an emerging technology is regarded as an essential technological landscape affecting nearly every transaction done over the internet. However, its role in RE is still unclear. Therefore, this study comprehensively explores the theory of blockchain and its status in the RE space. The review revealed that the integration of blockchain technology into RE has received significant attention over the years, which is an indication that existing blockchain research on energy is more focused on RE, as a way of addressing the many challenges in its evolution process, and providing sustainable solutions to replace energy from fossil fuels.
【Abstract】Purpose Large attention surrounds identifying the meaningful blockchain business model on financial services, while a little focus about non-financial organizations and solutions in terms of how the blockchain business model can affect the organization and bring more value. To address the complex structure of businesses that have public goods, it is important to develop sustainable blockchain-based business models. Design/methodology/approach This study offers the first qualitative research that uses an integrated technological, environmental and organizational (TOE) framework with technology acceptance theory (TAM) to study the adoption of blockchain technology by Spanish firms. Findings The results of the paper discuss how that competitive pressure, competence, top management support and relative advantage have a positive impact on intention to adopt blockchain technology while complexity affects the intention to adopt the technology negatively. Contrary to many adoption studies, the findings show that intention to adopt negatively impacts adoption and outline the effect of blockchain on business model elements on the macroeconomic level. Originality/value The key contribution of this study lies in providing a comprehensive understanding of the environmental, technological and organizational factors that impact the intention to adopt blockchain that eventually affects adoption.
【Abstract】Distributed Denial of Service (DDoS) attacks is always one of themajor problems for service providers. Using blockchain to detect DDoS attacksis one of the current popular methods. However, the problems of high time over-head and cost exist in the most of the blockchain methods for detecting DDoSattacks. This paper proposes a blockchain-based collaborative detection methodfor DDoS attacks. First, the trained DDoSattack detection model is encryptedby the Intel Software Guard Extensions (SGX), which provides high securityfor uploading the DDoS attack detection model to the blockchain. Secondly,the service provider uploads the encrypted model to Inter Planetary File System(IPFS) and then a corresponding Content-ID (CID) is generated by IPFS whichgreatly saves the cost of uploading encrypted models to the blockchain. In addi-tion, due to the small amount of model data, the time cost of uploading the DDoSattack detection model is greatly reduced. Finally, through the blockchain andsmart contracts, the CID is distributedto other service providers, who can usethe CID to download the corresponding DDoS attack detection model from IPFS.Blockchain provides a decentralized, trusted and tamper-proof environment forservice providers. Besides, smart contracts and IPFS greatly improve the distribu-tion efficiency of the model, while the distribution of CID greatly improves theefficiency of the transmission on the blockchain. In this way, the purpose of col-laborative detection can be achieved, and the time cost of transmission on block-chain and IPFS can be considerably saved. We designed a blockchain-basedDDoS attack collaborative detection framework to improve the data transmissionefficiency on the blockchain, and use IPFS to greatly reduce the cost of the dis-tribution model. In the experiment, compared with most blockchain-based methodfor DDoS attack detection, the proposed model using blockchain distributionshows the advantages of low cost and latency. The remote authentication mechan-ism of Intel SGX provides high security and integrity, and ensures the availabilityof distributed models.
【Abstract】In this brief, we conduct a complex-network analysis of the Bitcoin transaction network. In particular, we design a new sampling method, namely random walk with flying-back (RWFB), to conduct effective data sampling. We then conduct a comprehensive analysis of the Bitcoin network in terms of the degree distribution, clustering coefficient, the shortest-path length, connected component, centrality, assortativity, and the rich-club coefficient. We obtain several important observations including the small-world phenomenon, multi-center status, preferential attachment, and non-rich-club effect of the current network. This work brings up an in-depth understanding of the current Bitcoin blockchain network and offers implications for future directions in malicious activity and fraud detection in cryptocurrency blockchain networks.
【Abstract】A Virtual Power Plant (VPP) balances the load on a power grid by allocating power generated by various interconnected units during periods of peak demand. In addition, demand-side energy devices such as Electric Vehicles (EVs) and mobile robots can also balance energy supply and demand when effectively deployed. However, the fluctuation of energy generated by renewable resources makes balancing energy supply a challenging goal. This paper proposes a semi-decentralized robust network of electric vehicles (NoEV) integration system for power management in a smart grid platform. The proposed approach integrates an aggregator with EV fleets into a blockchain framework. The EVs execute a multi-stage algorithm to predict the power consumption based on a novel federated learning algorithm named Federated Learning for Qualified Local Model Selection (FL-QLMS). From the evaluation results, the proposed system requires 35% fewer transactions in short intervals and propagation delays than the previous approaches and achieves better network efficiency while maintaining a high level of security. Moreover, NoEV achieves a 5.7% lower root mean square error (RMSE) than the conventional approach for power consumption prediction, which is a significant improvement. In addition, the FL-QLMS approach outperforms state-of-the-art methods in terms of robustness to client-side attacks. The evaluation results also show that the performance of FL-QLMS is not affected when 10% to 40% percent of the models are manipulated.
【Abstract】We demonstrate a novel application of online transfer learning for a digital assets trading agent. This agent uses a powerful feature space representation in the form of an echo state network, the output of which is made available to a direct, recurrent reinforcement learning agent. The agent learns to trade the XBTUSD (Bitcoin versus US Dollars) perpetual swap derivatives contract on BitMEX on an intraday basis. By learning from the multiple sources of impact on the quadratic risk-adjusted utility that it seeks to maximise, the agent avoids excessive over-trading, captures a funding profit, and can predict the market's direction. Overall, our crypto agent realises a total return of 350%, net of transaction costs, over roughly five years, 71% of which is down to funding profit. The annualised information ratio that it achieves is 1.46.
【Keywords】Reinforcement learning; Transfer learning; Costs; Reservoirs; Time series analysis; Cryptography; Training; Online learning; transfer learning; echo state networks; recurrent reinforcement learning; financial time series
【Abstract】Identity (ID) management systems have evolved based on traditional data modelling and authentication protocols that are facing security, privacy, and trust challenges with the growth of Internet of Things (IoT). Research surveys reveal that blockchain technology offers special features of self-sovereign identity and cryptography that can be leveraged to address the issues of security breach and privacy leaks prevalent in existing ID management systems. Although research studies are recently exploring the suitability of blockchain based support to existing infrastructure, there is a lack of focus on IoT ecosystem in the secured ID management with data provenance of digital assets in businesses. In this paper, we propose a blockchain based ID management system for computing assets in an IoT ecosystem comprising of devices, software, users, and data operations. We design and develop a proof-of-concept prototype using a federated and distributed blockchain platform with smart contracts to support highly trusted data storage and secure authentication of IoT resources and operations within a business case scenario.
【Abstract】To deal with environmental uncertainty, organizations need resilience to respond to disruptions, such as changing market conditions or variations in demand or supply, while avoiding large scale adjustments. The concept of resilience is ambiguous, often explained as the capability of an organization or a supply chain to recover its original state, within an appropriate time frame, after being disrupted. Resilient supply chains have event handling capabilities, can provide efficient responses, and can return to their normal operating performance, after the disruptive event. To increase their resilience, companies often make changes or adjustments to their internal IT infrastructure, which may temporarily disrupt their smooth operation. As a result, contemporary IT infrastructures are mixed and include varied systems or technologies. Although new technologies, including blockchain, IoT and cloud-based solutions, may facilitate the handling of changes by providing secure, low cost and scalable solutions, more traditional systems may hinder such changes. Therefore, the relationship between IT and supply chain resilience is still unclear. The paper intends to examine the above issues by adopting a socio-technical approach to explain the concept of supply chain resilience and investigate the role of IT. More specifically, based on previous literature and on the appreciative systems thinking theoretical perspective, the paper develops a theoretical framework to analyse the organisational and/or supply chain resilience. It then uses this framework to examine and explain the impact of IT, by identifying important characteristics of an IT infrastructure and examining whether they may support or hinder business resilience.
【Abstract】Smart Healthcare (SHC) plays an increasingly greater role in improving the quality of health care, which has been widely concerned by researchers, hospitals and governments. In SHC, it is crucial that a patient's health data is readily accessible to authorized nurses, doctors, and emergency services. To realize the easy access while protecting the privacy of patients' data, ciphertext-policy attribute-based encryption (CP-ABE) has been widely used to achieve secure data sharing and support fine-grained access control. However, the existing CP-ABE schemes have three flaws for SHC. First, CP-ABE with partially hidden of access policies may also leak user's attribute privacy. Second, malicious user may disclose patient's health records and these records can not be traced. Third, it is less efficient that the data user, who does not have right to access data, downloads the whole ciphertext. In this paper, we design STEAC to address the above problems. To solve the first problem, we introduce the garbled Bloom filter method to realize fully hidden of access policies. For solving the second problem, we use the transaction-based blockchain scheme to trace the ciphertext storage and access. And before the real decryption, a decryption test operation is added to overcome the third flaw. Finally, security analysis and comprehensive performance evaluation also demonstrate STEAC is secure in standard model and is also more efficient than the previous schemes.
【Abstract】This paper studies how the blockchain technology applies the enterprise's vertical value chain management and specifically studies how the blockchain technology is applied to the management of various transaction information involved in the enterprise's vertical value chain management. This paper first analyzes the basic needs of the enterprise vertical value chain management, analyzes the decentralization, integrity, and authenticity of relevant transaction information in management, and designs and implements enterprise value chain management solution based on the blockchain technology, including the design and implementation of organizations, consensus mechanisms, data structures, and business processes. The simulation data is used for testing, and finally, the solution is evaluated in terms of security, transparency, efficiency, and scalability. The research in this paper shows that the blockchain technology can be applied to the enterprise's vertical value chain management, which can ensure the authenticity, transparency, tamper resistance, and security of various transaction information of enterprises, thus improving the quality and reliability of the vertical value chain management of enterprises.
【Abstract】In current generation the concept of cyber twin technology has been emerging as an improved platform for different applications. This paper emphasize on examining the effect of cyber twin technology for manufacturing equipment in Industry 4.0 applications by solving three different elementary objectives. For the proposed conception a new system model is identified for integrating triobjective cases with artificial intelligence algorithm. In addition, high security measures are also incorporated using blockchain technology which is one basic requirement for industrial applications for creating real twins. Both system model and algorithm have been combined for providing effective performance in real time using a physical entity. The effectiveness of the proposed model is tested with sensor prototype and simulated with four scenarios where the projected model provides better performance for more than 72% when compared with existing methodologies.
【Abstract】This study examines the volatility changes of 20 cryptocurrencies from January 2018 to May 2021 using sparse VHAR-MGARCH model. Our proposed model incorporates the high-dimensionality and time-varying conditional heterogeneity of cryptocurrency markets. We examined the time-varying spillover index, dynamic correlation structure, and connectivity between cryptocurrencies. Our empirical analysis clearly shows that there was a volatility shift on 13 March 2020, due to a market crash caused by COVID-19. This naturally divides the data into three periods: pre-crisis, during the crisis, and post-crisis regimes. The pre-crisis regime exhibited long-term cyclic fluctuations in the spillover index. However, after the market crash, the spillover index remained at a very high level with almost no interconnections between cryptocurrencies. The post-crisis regime showed quite a few irregular and sharp spikes in the spillover index, together with record-breaking prices and volumes.
