【Abstract】Blockchain (BC) applications in supply chain management (SCM) have recently received extensive attention. It is important to synthesise the extant literature on the field to identify key research themes and navigate potential future directions. This study thus develops an efficient, scalable data-driven review approach that uses text mining and Latent Dirichlet Allocation (LDA)-based topic modelling for automatic content analysis of full-text documents. Our method overcomes the drawbacks of traditional systematic literature reviews using either manual coding or bibliographic analysis for article classifications, which are highly time-consuming and biased when dealing with large amounts of text. 108 papers published between 2017 and 2022 were analysed which identified 10 key research themes, including revenue management, sustainability, traceability, manufacturing system, scheduling in cloud manufacturing, healthcare SCM, anti-counterfeit system, logistics and transportation, system architecture development, and food & agriculture SC. Five future directions are then suggested, including (1) integration of BC and other emerging technologies for global and scalable SCM, (2) crypto-X applications in SCM, (3) BC-enabled closed-loop SCM, (4) the environmental and social impacts of BC-based SCM and (5) decentralised autonomous organisations in SCM.
【Abstract】Addressing the blockchain technology (BCT) challenges, such as the high energy consumption is unavoidable in smart power systems to take maximum advantage. As an antithetical point, there is a structural duality between using BCT in the electrical grid due to its advantages and energy consumption. To this end, this research work is an inclination toward controlling the miner's energy consumption based on a realistic and efficacious two-stage energy mechanism toward the distributed energy concept and optimal placement of data mining devices. In this circumstance, such a new structure allows miners to mainly sustain their hash rates as a prominent index for security achievement and optimally decrease their cost. This paper suggests a novel distributed model for miners coincided with the smart electrical grid getting inspired by the Prima-Dual Method of Multipliers (PDMM) based distributed approach to settle down the needed power bartering between miners and energy supply resources. In addition, for a similar purpose, it seems to reach the ideal resolution needs to perform the modified reaffirmation of miners (the mining pool) within the secured grid. To execute this task, this research recommends the Intel-ligent Priority Selection (IPS) techniques as well. When all is said and done, the result of this approach can aid researchers with performing in the field of improving social advantages by the usage of the suggested method.
【Abstract】Problem definition: This paper provides a theoretical investigation into the value and design of a traceability-driven blockchain under different supply chain structures. Methodology/results: We use game theory to study the quality contracting equilibrium between one buyer and two suppliers and identify two fundamental functionalities of a traceability-driven blockchain. In serial supply chains, the ability to trace the sequential production process creates value by mitigating double moral hazard. In this case, traceability always improves product quality and all firms' profits and naturally creates a win-win. In parallel supply chains, the ability to trace the product origin enables flexible product recall, which can reduce product quality. In this case, traceability can benefit the buyer while hurting the suppliers, creating an incentive conflict. Managerial implications: Firms operating in different kinds of supply chains could face unique challenges when they adopt and design a traceability-driven blockchain. First, in serial supply chains, any firm can be the initiator of the blockchain, whereas in parallel supply chains, it may be critical for the buyer to take the lead in initiating the blockchain and properly compensate the suppliers. Second, in serial supply chains, a restricted data permission policy where each supplier shares their own traceability data with the buyer but not with each other can improve the supply chain profit, whereas in parallel supply chains, it is never optimal to restrict a firm's access to the traceability data. Third, the suppliers' incentive to enhance the governance of data quality is more aligned with the supply chain optimum in serial supply chains compared with parallel supply chains.
【Abstract】In recent years, many core technologies of Industry 4.0 have advanced significantly, particularly the integration of big data technology and cloud manufacturing (CMfg). The decentralization and traceability features of blockchain technology (BCT) provide an effective solution to provide trusted resource service in CMfg. Service composition is a core issue of CMfg to increase the value of digital assets. However, existing research on service composition based on BCT suffers from both the blockchain proof-of-work (PoW) mechanism and the service composition problem need to consume large computational overheads, as well as the blockchain fork problem affecting the system's reliability, which reduces the usefulness of these schemes. To solve these problems, this paper proposes a novel multi-objective service composition architecture for blockchain-based CMfg (MOSC-BBCM). In MOSC-BBCM, first, a blockchain-chained storage structure is designed for the actual manufacturing cloud service constraint and scale dynamic changes, which can fully use the historical service information and accelerate the search for high-quality solutions. Second, to reduce the squandered computing resources in the PoW, a mining mechanism based on multi-objective service composition and optimal selection is proposed, where miners competitively solve a nondeterminate polynomial-hard problem to replace the mathematical puzzle. Finally, an incentive mechanism based on the environment selection method is proposed, which can avoid the fork problem while distributing on a labor basis. The effectiveness of the proposed MOSC-BBCM is verified in simulated numerical experiments of CMfg, which shows that the architecture provides a flexible and configurable scheme for blockchain-based CMfg with high availability.
【Abstract】Over the years, the popularity and usage of wearable Internet of Things (IoT) devices in several healthcare services are increased. Among the services that benefit from the usage of such devices is predictive analysis, which can improve early diagnosis in e-health. However, due to the limitations of wearable IoT devices, challenges in data privacy, service integrity, and network structure adaptability arose. To address these concerns, we propose a platform using federated learning and private blockchain technology within a fog-IoT network. These technologies have privacy-preserving features securing data within the network. We utilized the fog-IoT network's distributive structure to create an adaptive network for wearable IoT devices. We designed a testbed to examine the proposed platform's ability to preserve the integrity of a classifier. According to experimental results, the introduced implementation can effectively preserve a patient's privacy and a predictive service's integrity. We further investigated the contributions of other technologies to the security and adaptability of the IoT network. Overall, we proved the feasibility of our platform in addressing significant security and privacy challenges of wearable IoT devices in predictive healthcare through analysis, simulation, and experimentation.
【Keywords】Internet of Things; Wearable computers; Medical services; Federated learning; Servers; Data privacy; Security; distributed systems; fog network; health care services; health informatics; Internet of Things (IoT); machine learning; platforms; predictive models; privacy; private blockchain; scalability; security; testbed
【Abstract】Nowadays, securely sharing medical data is one of the significant concerns in blockchain technology. The existing blockchain approaches have faced high time consumption, low confidentiality, and high memory usage for transferring the file in a secure way because of attack harmfulness and large unstructured records. It has ended in security threat, so the integrity of the user data has been lost. Hence, a novel hybrid Deep Belief-based Diffie Hellman (DBDH) security framework was presented to protect medical data from malicious events. Incorporating a deep belief neural system continuously monitors the system and identifies the attacks. Initially, the IoMT dataset was collected from the standard site and imported into the system. Moreover, hash 1 was calculated for the original data and stored in the cloud server for verification. Then, the original data was encrypted with a private key for data hiding. The incorporation of homomorphic property helps to calculate hash 2 for encrypted data. Finally, in the verification module, both hash values are verified. In addition, cryptanalysis was performed by launching an attack to validate the performance of the designed model. Moreover, the estimated outcomes of the presented model were compared with existing approaches to determine the improvement score.
【Abstract】As one of the emerging technologies that have attracted much attention, blockchain has a wide range of application prospects. However, one prominent issue restricting its development is the limited transaction throughput. Take the well-known open-source system Hyperledger Fabric as an example. In the solution of parallel transaction processing, it follows the processing method of MVCC in the database, which is not compatible with blockchain features, resulting in a sharp drop in throughput and wastes of storage space in high concurrency scenarios. In this paper, we propose a high-throughput optimization scheme FabricETP that can effectively solve concurrency conflicts. According to the different causes of conflicts, FabricETP proposes optimization ideas from two dimensions. For transaction conflicts within a block, FabricETP proposes a scheduling algorithm to minimize the number of conflicting transactions by rearranging the transaction execution order. For transaction conflicts between blocks, FabricETP has established a cache-based conflict transaction avoidance mechanism, so that invalid transactions are aborted early. With the help of general blockchain performance testing tools, we carry out experiments under various workload scenarios. The results show that the throughput of FabricETP can reach up to 9.51 x that of the benchmark blockchain system Fabric and 1.26 x of the optimized version of Fabric + + under high concurrency scenarios. Compared with Fabric + + , the space utilization is increased by 20%.
【Abstract】The Internet of Things (IoT) is a network of interconnected computing devices with unique IDs and the potential to exchange data over the network. Most current IoT solutions have highly centralized designs vulnerable to cyber-attacks and have a single point of failure. A new solution path is required to improve data access by enhancing privacy and security standards. In this research, the Block Chain-based sensor system was designed for an embedded IoT platform to improve the integrity of sensor data with their open issues and challenges. The main objective of this research is to enhance sensor data security, resolve single points of failures and improve the trust between users to make the framework more scalable for devices. In this review paper, BC-based IoT network-based techniques are analyzed based on the security and privacy-preservation aspects. Also, discuss current research obstacles and suggest some study possibilities for future work.
【Abstract】Mobile crowdsensing (MCS), as a novel large-scale data acquisition method, has attracted more and more attention. Since the participants' quality directly affects the quality of perceptual task completion in MCS, participant selection has become a focus of researchers. However, due to the sparsity of participants' information and data privacy, existing solutions have certain limitations in terms of security and accuracy in participant selection. To tackle these problems, this paper proposes a secure and accurate participant selection (SAPS) method. It employs blockchain-based cross-domain reputation sharing while labeling participants with personalized reputation tags as quality references to achieve security and accuracy in participant selection. In particular, SAPS utilizes a model of differential privacy to protect privacy during cross-domain sharing while guaranteeing the credibility of the data sources by leveraging the traceability and non-tamper nature of the blockchain. Comprehensive experiments on real datasets indicate that compared with CMABA, the tasks' completion quality in SAPS is improved by 18%, and the execution cost of SAPS is reduced by 6%.
【Abstract】The uncontrollable spread of contagious disease COVID-19 is a perennial threat to mankind and has resulted in an unprecedented lockdowns in several countries including Pakistan which in turn has caused an adverse socio-economic impact to all industries. The strategic leadership and concerned state authorities are trying hard to combat and control the spread of COVID-19 pandemic. The effective use of Information Management & Decision Support (IMDS) System can play significant role in combating pandemic and its spread, managing relief actions effectively, accessing vulnerable communities to roll out targeted subsidies by ensuring the coordinated effort and subsequent implementation. Reliable information is significantly critical to assist government and public health agencies in determining the best way forward to control this global health emergency. Therefore, this paper aims to strengthen capacity of IMDS System used by government institutions and authorities for decision making and information dissemination. In this research work, we addressed the integrity-based issues that include completeness, correctness, and freshness of data by proposing a block chain-based integrity protection mechanism. The proposed novel framework is a cascaded formulation of Integrity Assurance (IA) Protocol, Cryptographic Merkle Hash Tree, Digital Signature, and Blockchain. Beside cascaded formulation, two (2) schemes for MHT Generation are also presented in the framework. The proposed framework ensures fairness, completeness, and correctness of data that will be very helpful for secure data management, integration, and utilization in analysis for decision-making. The proposed framework achieved an accuracy of more than 98.09% with better quantitative performance in standard evaluation parameters.
【Abstract】Technological innovation generates products, services, and processes that can disrupt existing industries and lead to the emergence of new fields. Distributed ledger technology, or blockchain, offers novel transparency, security, and anonymity characteristics in transaction data that may disrupt existing industries. However, research attention has largely examined its application to finance. Less is known of any broader applications, particularly in Industry 4.0. This study investigates academic research publications on blockchain and predicts emerging industries using academia-industry dynamics. This study adopts latent Dirichlet allocation and dynamic topic models to analyze large text data with a high capacity for dimensionality reduction. Prior studies confirm that research contributes to technological innovation through spillover, including products, processes, and services. This study predicts emerging industries that will likely incorporate blockchain technology using insights from the knowledge structure of publications.
【Abstract】MainElectronic health record (EHR) applications are digital versions of paper-based patient health information. Traditionally, medical records are made on paper. However, nowadays, advances in information and communication technology have made it possible to change medical records from paper to EHR. Therefore, preserving user data privacy is extremely important in healthcare environments. The main challenges are providing ways to make EHR systems increasingly capable of ensuring data privacy and at the same time not compromising the performance and interoperability of these systems.Subject and methodsThis systematic mapping study intends to investigate the current research on security and privacy requirements in EHR systems and identify potential research gaps in the literature. The main challenges are providing ways to make EHR systems increasingly capable of ensuring data privacy, and at the same time, not compromising the performance and interoperability of these systems. Our research was carried out in the Scopus database, the largest database of abstracts and citations in the literature with peer review.ResultsWe have collected 848 articles related to the area. After disambiguation and filtering, we selected 30 articles for analysis. The result of such an analysis provides a comprehensive view of current research.ConclusionsWe can highlight some relevant research possibilities. First, we noticed a growing interest in privacy in EHR research in the last 6 years. Second, blockchain has been used in many EHR systems as a solution to achieve data privacy. However, it is a challenge to maintain traceability by recording metadata that can be mapped to private data of the users applying a particular mapping function that can be hosted outside the blockchain. Finally, the lack of a systematic approach between EHR solutions and existing laws or policies leads to better strategies for developing a certification process for EHR systems.
【Abstract】The Internet of Things is an essential component in the growth of an ecosystem that enables quick and precise judgments to be made for communication on the battleground. The usage of the battlefield of things (BoT) is, however, subject to several restrictions for a variety of reasons. There is a potential for instances of replay, data manipulation, breaches of privacy, and other similar occurrences. As a direct result of this, the implementation of a security mechanism to protect the communication that occurs within BoT has turned into an absolute requirement. To this aim, we propose a blockchain-based solution that is both safe and private for use in communications inside the BoT ecosystem. In addition, research is conducted on the benefits of integrating blockchain technology and cybersecurity into BoT application implementations. This work elaborates on the importance of integrating cybersecurity and blockchain-based tools, techniques and methodologies for BoT.
