【Author】 Madni, Hussain Ahmad Umer, Rao Muhammad Foresti, Gian Luca

【Source】INTERNATIONAL JOURNAL OF NEURAL SYSTEMS CCF-C

【影响因子】6.325

【主题类别】

区块链技术-协同技术-联邦学习

【Abstract】Swarm Learning (SL) is a promising approach to perform the distributed and collaborative model training without any central server. However, data sensitivity is the main concern for privacy when collaborative training requires data sharing. A neural network, especially Generative Adversarial Network (GAN), is able to reproduce the original data from model parameters, i.e. gradient leakage problem. To solve this problem, SL provides a framework for secure aggregation using blockchain methods. In this paper, we consider the scenario of compromised and malicious participants in the SL environment, where a participant can manipulate the privacy of other participant in collaborative training. We propose a method, Swarm-FHE, Swarm Learning with Fully Homomorphic Encryption (FHE), to encrypt the model parameters before sharing with the participants which are registered and authenticated by blockchain technology. Each participant shares the encrypted parameters (i.e. ciphertexts) with other participants in SL training. We evaluate our method with training of the convolutional neural networks on the CIFAR-10 and MNIST datasets. On the basis of a considerable number of experiments and results with different hyperparameter settings, our method performs better as compared to other existing methods.

你可以尝试使用大模型来生成摘要 立即生成

【Keywords】Swarm learning; fully homomorphic encryption; federated learning; gradient leakage

【发表时间】2023

【收录时间】2023-06-20

【文献类型】 实验仿真

【DOI】 10.1142/S0129065723500338

【Author】 Ren, Yi-Shuai Ma, Chao-Qun Kong, Xiao-Lin Baltas, Konstantinos Zureigat, Qasim

【Source】RESEARCH IN INTERNATIONAL BUSINESS AND FINANCE

【影响因子】6.143

【主题类别】

区块链技术-协同技术-机器学习

【Abstract】Cryptocurrency has captured the interest of financial scholars and become a major research topic in blockchain. In cryptocurrency research, the use of machine learning algorithms is enabled by the presence of many types of data and abundant resources. However, there is currently no comprehensive review on cryptocurrencies using machine learning. Therefore, we collect papers on cryptocurrency-related using machine learning in the web of science database, and summarize these papers according to the algorithm, and draw the following conclusions: (1) The application of machine learning for cryptocurrencies research is increasing year over year; (2) Predicting cryptocurrency price trends and income fluctuations is the most relevant research topic; (3) The machine learning algorithm utilized in cryptocurrency research is not unique, and the practise of combining multiple machine learning approaches has emerged; (4) Concerns such as overfitting and interpretability still persist with machine learning methods. Finally, we suggest future research directions.

你可以尝试使用大模型来生成摘要 立即生成

【Keywords】Cryptocurrency; Machine learning; Blockchain; Bibliometric analysis

【发表时间】2022

【收录时间】2023-06-20

【文献类型】 综述

【DOI】 10.1016/j.ribaf.2022.101799

【Author】 Mohammed, Abubakar Potdar, Vidyasagar Quaddus, Mohammed

【Source】FOODS

【影响因子】5.561

【主题类别】

区块链应用-实体经济-供应链

【Abstract】Blockchain technology (BCT) has been proven to have the potential to transform food supply chains (FSCs) based on its potential benefits. BCT promises to improve food supply chain processes. Despite its several benefits, little is known about the factors that drive blockchain adoption within the food supply chain and the impact of blockchain technology on the food supply chain, as empirical evidence is scarce. This study, therefore, explores factors, impacts and challenges of blockchain adoption in the FSC. The study adopts an exploratory qualitative interview approach. The data consist of Twenty-one interviews which were analyzed using thematic analysis techniques in NVivo (v12), resulting in identifying nine factors classified under three broad categories (Technology-complexity, compatibility, cost; Organization-organization size, knowledge; Environment-government support, competitive pressure, standardization, and compliance) as the most significant factors driving blockchain adoption in the FSC. In addition, five impacts were identified (visibility, performance, efficiency, trust, and value creation) to blockchain technology adoption. This study also identifies significant challenges of blockchain technology (interoperability, privacy, infrastructure conditions, and lack of knowledge). Based on the findings, the study developed a conceptual framework for blockchain adoption in food supply chains. The study adds to the corpus of knowledge by illuminating the adoption of blockchain technology and its effects on food supply chains and by giving the industry evidence-based guidance for developing its blockchain plans. The study provides full insights and awareness of blockchain adoption challenges among executives, supply chain organizations, and governmental agencies.

你可以尝试使用大模型来生成摘要 立即生成

【Keywords】blockchain; food supply chain; adoption framework; challenges; impacts

【发表时间】2023

【收录时间】2023-06-20

【文献类型】 理论模型

【DOI】 10.3390/foods12102052

【Author】 Liu, Yulin He, Debiao Bao, Zijian Wang, Huaqun Khan, Muhammad Khurram Choo, Kim-Kwang Raymond

【Source】IEEE TRANSACTIONS ON INTELLIGENT VEHICLES

【影响因子】5.009

【主题类别】

区块链应用-实体经济-车联网

【Abstract】Vehicle-to-Grid (V2G) networks are potential solutions to addressing energy and environmental challenges, although security remains a key concern. For example, attackers may seek to obtain private information from frequent electricity/service exchanges between electric vehicles (EVs) and smart grids (SG) in V2G networks. While there have been successful attempts in using ring signatures to achieve privacy-preserving payment and ensure reliable services in V2G many existing ring signature-based payment proposals has significant signature size. To address the aforementioned problem, we propose Emularis, an efficient multilayered linkable ring signature scheme with a logarithmic size. We also implement an anonymous payment scheme for V2G using Emularis. We then prove that Emularis guarantees security and privacy requirements through rigorous security analysis. Furthermore, our scheme significantly outperforms existing schemes in terms of communication and computation costs. Extensive experimental results indicate that our scheme is suitable for the deployment in V2G security-related applications.

你可以尝试使用大模型来生成摘要 立即生成

【Keywords】Vehicle-to-grid; Privacy; Protocols; Security; Cryptocurrency; Authentication; Public key; Anonymous payment; privacy preservation; ring signature; V2G networks

【发表时间】2023

【收录时间】2023-06-20

【文献类型】 实验仿真

【DOI】 10.1109/TIV.2022.3216949

【Author】 Gao, Yi-Ling Gong, Bengang Liu, Zhi Tang, Juan Wang, Chengfu

【Source】INDUSTRIAL MANAGEMENT & DATA SYSTEMS

【影响因子】4.803

【主题类别】

区块链应用-实体经济-供应链

【Abstract】PurposeRecycling and reuse of the electric vehicle (EV) batteries are ways to extend their limited lives. If batteries can be traced from production to recycling, it is beneficial for battery recycling and reuse. Using blockchain technology to build a smart EV battery reverse supply chain can solve the difficulties of lack of trust and data. The purpose of this study is to discuss the behavioural evolution of a smart EV battery reverse supply chain under government supervision.Design/methodology/approachThis study adopts evolutionary game theory to examine the decision-making behaviours of the government, EV manufacturers with recycled used batteries and third-party EV battery recyclers lacking professional recycling qualification.FindingsOn the smart reverse supply chain integrated by blockchain technology, a cooperative recycling strategy of the third-party EV battery recycler is the optimal choice when the government tends to actively regulate. The probability of the EV manufacturer choosing the blockchain adoption strategy exceeds (below) the threshold, and the government prefers negative (positive) supervision. According to numerical analysis, in the mature stage in the EV battery recycling industry, when the investment cost of applying blockchain is high, EV manufacturers' willingness to apply blockchain slows down, the government accelerates adopting a negative supervision strategy and third-party EV battery recyclers prefer cooperative recycling.Practical implicationsThe results of this study provide opinions on the strength of government supervision and the conditions under which EV manufacturers and third-party EV battery recyclers should apply blockchain and cooperate. On the other hand, this study provides theoretical analysis for promoting the application of blockchain technology in smart reverse supply chain.Originality/valueCompared with previous research, this study reveals the relevance of government supervision, blockchain application and cooperation strategy in smart EV battery reverse supply chain. In the initial stage, even if the subsidy (subsidy reduction rate) and penalty are high and the penalty reduction rate is low, the EV manufacturer should rather give up the application of blockchain technology. In the middle stage in the EV battery recycling industry, the government can set a lower subsidy (subsidy reduction rate) combined with a penalty or a higher penalty (penalty reduction rate) combined with a subsidy to supervise it. The third-party EV battery recycler is advised to cooperate with the EV manufacturer when the subsidy is low or the penalty is high.

你可以尝试使用大模型来生成摘要 立即生成

【Keywords】EV battery recycling; Blockchain application; Evolutionary game; Government supervision; Cooperation strategy

【发表时间】2023

【收录时间】2023-06-20

【文献类型】 理论模型

【DOI】 10.1108/IMDS-10-2022-0639

【Author】 Sakas, Damianos P. Giannakopoulos, Nikolaos T. Nasiopoulos, Dimitrios K. Kanellos, Nikos Tsoulfas, Giannis T.

【Source】SUSTAINABILITY

【影响因子】3.889

【主题类别】

区块链应用-实体经济-供应链

【Abstract】Recent developments in blockchain technology have enabled the development of wallet applications for storing peoples' cryptocurrency reserves. Cryptocurrency wallet applications could deploy affiliate marketing processes to increase the visibility of their products. From these affiliate marketing processes, supply chain firms in the air forwarding sector that seek to advertise their services to a larger audience could be benefited. This research examines whether affiliate marketing initials of cryptocurrency wallet applications affect their digital marketing efficiency, as well as whether air forwarding firms' website visibility could be benefited from them. After collecting the required Web Analytic data, the authors performed statistical analysis (correlations and linear regressions), followed by Fuzzy Cognitive Mapping (FCM) macroanalysis and Hybrid Modeling (HM) microanalysis to assess the outcomes of cryptocurrency wallet applications' affiliate marketing programs. Hence, from the deployed methodology, valuable insights arose. The first part of the produced outcomes concerns the effect of cryptocurrency wallet application affiliate marketing metrics on their digital marketing results. The increased implications of affiliate marketing metrics (referring domains, backlinks, etc.) decrease the number of pages their visitors see. Regarding the air forwarder firms' website visibility, specific metrics (branded and referral traffic) were increased and others (social traffic) were decreased from the increment of cryptocurrency wallet application affiliate marketing metrics (backlinks, internal links, etc.). Supply chain firms, in the air forwarding sector, could have increased website visibility by deploying advertisements and affiliate marketing initiatives with cryptocurrency wallet organizations. Summing up, specific affiliate marketing metrics of cryptocurrency wallet applications are capable of significantly impacting their digital marketing performance and also constitute determinant factors of supply chain firms' website visibility.

你可以尝试使用大模型来生成摘要 立即生成

【Keywords】strategic digital marketing; digitalization; sustainability; supply chain; innovation; process optimization; blockchain; big data; Decision Support Systems (DSSs)

【发表时间】2023

【收录时间】2023-06-20

【文献类型】 实证数据

【DOI】 10.3390/su15097326

【Author】 Kumar, C. U. Om Gajendran, Sudhakaran Balaji, V. Nhaveen, A. Balakrishnan, S. Sai

【Source】SOFT COMPUTING CCF-C

【影响因子】3.732

【主题类别】

区块链应用-实体经济-医疗领域

【Abstract】Transferring of data in machine learning from one party to another party is one of the issues that has been in existence since the development of technology. Health care data collection using machine learning techniques can lead to privacy issues which cause disturbances among the parties and reduces the possibility to work with either of the parties. Since centralized way of information transfer between two parties can be limited and risky as they are connected using machine learning, this factor motivated us to use the decentralized way where there is no connection but model transfer between both parties will be in process through a federated way. The purpose of this research is to investigate a model transfer between a user and the client(s) in an organization using federated learning techniques and reward the client(s) for their efforts with tokens accordingly using blockchain technology. In this research, the user shares a model to organizations that are willing to volunteer their service to provide help to the user. The model is trained and transferred among the user and the clients in the organizations in a privacy preserving way. In this research, we found that the process of model transfer between user and the volunteered organizations works completely fine with the help of federated learning techniques and the client(s) is/are rewarded with tokens for their efforts. We used the COVID-19 dataset to test the federation process, which yielded individual results of 88% for contributor a, 85% for contributor b, and 74% for contributor c. When using the FedAvg algorithm, we were able to achieve a total accuracy of 82%.

你可以尝试使用大模型来生成摘要 立即生成

【Keywords】COVID-19; CT scan images; Federated learning; Blockchain; VGG-16; AlexNet; Inception (V3)

【发表时间】2023

【收录时间】2023-06-20

【文献类型】 实验仿真

【DOI】 10.1007/s00500-023-08330-6

【Author】 Mhiri, Mariem Al-Yafi, Karim Legros, Benjamin Jouini, Oualid Haouari, Mohamed

【Source】INTERNATIONAL TRANSACTIONS IN OPERATIONAL RESEARCH

【影响因子】3.610

【主题类别】

区块链应用-实体经济-供应链

【Abstract】We address two interrelated issues affecting the hinterland portion of the maritime container supply chain: reducing the movement of empty containers and reducing empty trips by trucks carrying these containers. In this paper, we show that empty container flow optimization can be implemented via a blockchain based on the proof-of-useful-work concept where the proof of work requires the solution of an NP$\mathcal{NP}$-hard optimization problem whose solution benefits the blockchain participants. Accordingly, we propose that anonymous miners compete to solve the container truck routing problem, which seeks to find the most efficient routes for trucks. We show that this problem is NP$\mathcal{NP}$-hard. Miners must also solve the problem of optimally matching consignees and shippers, which will reduce transportation and storage costs for empty containers. In essence, the proposed framework turns blockchain into a massive optimization engine that directly benefits the hinterland container supply chain ecosystem.

你可以尝试使用大模型来生成摘要 立即生成

【Keywords】container supply chain; prize collecting vehicle routing problem; blockchain; proof of useful work

【发表时间】2023

【收录时间】2023-06-20

【文献类型】 理论模型

【DOI】 10.1111/itor.13319

【Author】 Wang, Junlu Li, Su Wanting, Ji Li, Dong Song, Baoyan

【Source】PEER-TO-PEER NETWORKING AND APPLICATIONS CCF-C

【影响因子】3.488

【主题类别】

区块链技术-协同技术-数据管理

【Abstract】The existing blockchain system mostly adopts the equal mining mode. All bookkeepers (entities) record the ledgers on a single main chain, and the data storage is random. Moreover, in complex or classified financial scenarios, the data of the main chain is difficult to realize association or regular storage, resulting in low efficiency of storage and query. At the same time, in the existing blockchain system, event traceability is mostly only found in the source block, and the implicit association between entities cannot be identified, so the query has limitations. To solve these problems, this paper proposes a composite blockchain associated event tracing method. This method firstly constructs the blockchain composite chain storage structure model, proposes the concept of private chain and alliance chain, and realizes the adaptive data association storage in complex or classified scenarios. Secondly, on the basis of obtaining the event source entity block, the auxiliary storage space is established to transfer storage relevant data. A tracing method of associated entity block based on the Apriori algorithm is proposed, and then the obtained traceability entity block is constructed as the source event correlation graph, so as to describe the association relationship between the event entities. Finally, a risk assessment system based on reinforcement learning is proposed to realize the risk assessment of traceability entity. Experiments show that the composite blockchain associated event tracing method proposed in this paper can reduce 60% of the storage overhead, improve 90% of the query accuracy and 50% of the security. can reduce the storage overhead by 60%, improve the query accuracy by 90% and improve security by 50%.

你可以尝试使用大模型来生成摘要 立即生成

【Keywords】Composite chain structure; Private chain; Alliance chain; Traceability of associated events; Reinforcement learning

【发表时间】2023

【收录时间】2023-06-20

【文献类型】 实验仿真

【DOI】 10.1007/s12083-023-01469-x

【Author】 Angelin, P. Blessed Franklin, S. Wilfred

【Source】TRANSACTIONS ON EMERGING TELECOMMUNICATIONS TECHNOLOGIES

【影响因子】3.310

【主题类别】

区块链应用-实体经济-医疗领域

【Abstract】Blockchain is a reliable ledger database that may be used to store various private healthcare data, but uploading and sharing data is difficult due to privacy concerns. Hence, to overcome these issues, a novel HCCLO with master Birch-Brown Paruvala-SLSTM model has been proposed to store various patients' medical data and shield it from threats. Hyper Contour Cryptography with Lepidoptera Optimization (HCCLO) has been proposed in this model, which encrypts data to reduce unwanted time stamp creation and prevent private key theft. Also, the Master Birch-Brown-Parulava NN design is introduced to prevent a false identity that leads to a data breach, and it allows for private exchange and enhances framework reconciliation, acting as an immune response to information breaks in the chain and preventing data breaches from spreading further. Then, the SLSTM layer implant RF Classifier is introduced to categorize data as user requests and attacks, safeguarding the blocks against changeability caused by malware attacks. The proposed approach offers minimal block mine time, maximum accuracy, and healthcare data security.

你可以尝试使用大模型来生成摘要 立即生成

【Keywords】

【发表时间】2023

【收录时间】2023-06-20

【文献类型】 实验仿真

【DOI】 10.1002/ett.4799

【Author】 Wang, Xifeng Zhu, Hongsong Xiao, Han Zhou, Zan Yang, Shujie Sun, Limin

【Source】TRANSACTIONS ON EMERGING TELECOMMUNICATIONS TECHNOLOGIES

【影响因子】3.310

【主题类别】

区块链应用-实体经济-车联网

【Abstract】The rapid development and increasing popularity of mobile devices have facilitated the development of computation-intensive applications and services, but their constrained compute, storage and battery capabilities have also created the requirements for optimized resource provision and service orchestration. Emerging mobile edge computing (MEC) and next-generation networks (6G) can meet these requirements of mobile devices by migrating complex computing tasks and large volumes of data to edge servers with acceptable latency, thus effectively enhancing the quality of experience (QoE) of mobile users. Intelligent Vehicular Collaboration, as an intelligent mobile application or service in intelligent connected vehicle (ICV) applications, enables precise and effective driving decisions based on a large amount of real-time traffic information statistics and intelligent analysis of vehicle status to improve the user driving experience and the efficiency of intelligent transportation systems(ITS). However, the openness and dynamics of wireless communications and the high frequency of information interaction of MEC-enabled intelligent vehicular collaboration services in the 6G era make them highly vulnerable to cyber attacks. How to achieve dynamically trustworthy, secure, and intelligent vehicular collaboration services in the presence of malicious node access and cyber attacks in the 6G MEC-enabled vehicular network is a significant challenge. In this paper, we propose a novel blockchain-enabled trust management mechanism to address this challenge. First, we design a spatiotemporal-correlated message credibility assessment method and a dynamic mutual trust evaluation method to obtain accurate ratings for messages and mobile nodes respectively. Based on the above methods, we propose an improved blockchain-based intelligent trust management mechanism that enables transparent, tamper-evident, and trustworthy secure intelligent vehicular collaboration services while maintaining stable and efficient system performance. Simulation results show that our suggested solutions can efficiently evaluate the trust level of ICVs and achieve efficient and secure intelligent vehicular collaboration with acceptable communication and computation overheads.

你可以尝试使用大模型来生成摘要 立即生成

【Keywords】

【发表时间】2023

【收录时间】2023-06-20

【文献类型】 实验仿真

【DOI】 10.1002/ett.4791

【Author】 Colak, Haldun Kagnicioglu, Celal Hakan

【Source】JOURNAL OF BUSINESS-TO-BUSINESS MARKETING

【影响因子】3.045

【主题类别】

区块链治理-市场治理-技术采用

【Abstract】PurposeBlockchain technology is one of the candidate technologies for resolving supply chain issues that may occur as a result of the complex and continuously changing market structures of the present day. In addressing the problems encountered in such a system, blockchain technology has emerged as a target technology due to its notable advantages, such as smart contracts and product traceability. Since a supply chain consists of suppliers, manufacturers, retailers, and industrial customers, blockchain technology can be considered inter-firm technology. However, the literature mainly focuses on technical, individual, and environmental aspects of technology acceptance depending on technology acceptance theories. Therefore, more information is needed about how inter-firm relations and their aspects affect organizational blockchain technology acceptance. Consequently, this study aims to identify the inter-firm characteristics and their influence on the acceptance of blockchain technologies in supply chains using network theory.MethodologyThe research methodology design consists of two elements. First, based on the expert judgments, the relationships between the indicated parameters regarding blockchain acceptance intention are analyzed using the DEMATEL technique, based on expert opinion. In the second part, with the data obtained from 361 supply chain managers, the validity of the linked assumptions in the proposed model is confirmed by applying PLS-SEM.FindingsThe present study enhances our knowledge of inter-firm technology acceptance behavior by incorporating trading partner trust, initial firm power, the dependency between partners, knowledge sharing, and cooperation. According to the findings of DEMATEL, there is a strong association between inter-firm technology acceptance characteristics in explaining behavioral intention. Whereas other variables mainly influence dependency, trust has the most significant impact on those variables with cooperation. On the other hand, PLS-SEM analysis delivers remarkable results that describe the complicated structure of blockchain acceptance from an inter-firm perspective. Cooperation is the most influential variable affecting behavioral intention (0.614), followed by dependency (0.156) and knowledge sharing (0.153). Even though the direct effects of inter-firm trust and the initial firm's power on behavioral intention were found insignificant, dependency fully mediates the effects of these variables on behavioral intention. Similarly, the relationship between trading partner trust and behavioral intention is fully mediated by knowledge sharing, while it also partially mediates the influence of cooperation. Examining the direct impacts reveals that cooperation is the most influential variable on behavioral intention, which is consistent with the DEMATEL conclusion.Research ImplicationsThe current study demonstrates that the network theory is appropriate for explaining the acceptance of blockchain technology from an inter-firm perspective within the context of supply chain interactions. Since the theory can delve into the underlying characteristics of these relationships, it helps justify the target behavior. On the other hand, the DEMATEL approach validates the relationships between variables in the theoretical model. Then these associations are verified using PLS-SEM considering the primary data obtained from supply chain managers. The primary purpose of the DEMATEL method was to elucidate the relationships between variables and provide empirical support for the structure of the theoretical model. The networks of linkages that developed from the DEMATEL approach based on expert opinions corroborate the relationships in the theoretical model based on the literature, suggesting a significant connection between the two methodologies. Such methodological designs are essential for boosting the results' trustworthiness and applicability.Practical ImplicationsCooperation is the most significant explanatory variable regarding blockchain technology acceptance. Following the nature of the supply chain, this conclusion highlights the significance of relationships between partners in chain. In their projects for blockchain technology, managers should examine the benefits of these technologies for themselves and other stakeholders in the chain. This study demonstrates issues with the inter-firm acceptance of blockchain technologies regarding the influence of trust and power on the final acceptance behavior. Nevertheless, the growth in inter-firm dependence enhances the efficiency of these effects. Therefore, managers must understand how to utilize their resources for chain gain. While this makes it easier for them to preserve their authority and influence the conduct of their partners over the long run, the appropriate allocation of resources across dependent stakeholders will ultimately strengthen the perception of trust. Our results also prove that knowledge sharing increases the effects of cooperation and inter-firm trust on behavioral intention. This indicates that managers should convince the other partners about the benefits of target technology by sharing key and timely information.OriginalityThis study makes numerous original contributions and provides new insights. This study contributes to general knowledge of the acceptance of blockchain technologies in the supply chain by focusing on the inter-firm technology perspective. In this vein, the results produced through the investigation of mediation relations are novel and presented to the literature. On the other hand, DEMATEL and PLS-SEM are integrated for the first time considering blockchain acceptance in supply chain studies, to our knowledge. Furthermore, this is the first study to combine network theory and inter-firm perspective to explain the acceptance of blockchain technology in supply chains.

你可以尝试使用大模型来生成摘要 立即生成

【Keywords】Supply chains; inter-firm blockchain acceptance; DEMATEL; PLS-SEM

【发表时间】2023

【收录时间】2023-06-20

【文献类型】 实证数据

【DOI】 10.1080/1051712X.2023.2214543

【Author】 Almalki, Jameel

【Source】ARABIAN JOURNAL FOR SCIENCE AND ENGINEERING

【影响因子】2.807

【主题类别】

区块链应用-实体经济-医疗领域

【Abstract】Existing blockchain approaches exhibit a diverse set of dimensions, and on the other hand, IoT-based health care applications manifest a wide variety of requirements. The state-of-the-art analysis of blockchain concerning existing IoT-based approaches for the healthcare domain has been investigated to a limited extend. The purpose of this survey paper is to analyze current state-of-the-art blockchain work in several IoT disciplines, with a focus on the health sector. This study also attempts to demonstrate the prospective use of blockchain in healthcare, as well as the obstacles and future paths of blockchain development. Furthermore, the fundamentals of blockchain have been thoroughly explained to appeal to a diverse audience. On the contrary, we analyzed state-of-the-art studies from several IoT disciplines for eHealth, and also the study deficit but also the obstacles when considering blockchain to IoT, which are highlighted and explored in the paper with suggested alternatives.

你可以尝试使用大模型来生成摘要 立即生成

【Keywords】Blockchain; Internet of things; Blockchain of things; Edge computing; HealthCare; Software engineering

【发表时间】2023

【收录时间】2023-06-20

【文献类型】 综述

【DOI】 10.1007/s13369-023-07896-5

【Author】 Manjaragi, Shivanand V. Saboji, S. V.

【Source】WIRELESS NETWORKS CCF-C

【影响因子】2.701

【主题类别】

区块链技术-协同技术-身份验证

【Abstract】In the fifth generation (5G), ultra-dense heterogeneous network (UDHN) is considered as a prominent technology to resolve network system problems. It is challenged to provide secure access since the UDHN contains access points (APs), user equipment (UE) which are characterized with the nature of dynamic, temporary as well as autonomy. The coverage of AP is less when compared to that of classical base station and the problem arises with the interaction between APs and UE during the mobility of UE. In order to attain efficient key agreement with fast and subsequent authentication, a new consensus mechanism has been proposed. By integrating the reinforcement learning method with the actor-critic learning based on fuzzy neural network (RLAC-FNN), blockchain-enabled handover authentication is enabled in 5G heterogeneous Networks. In the proposed method, the user can establish a secure and quick connection by excluding re-authentication and handover operators between heterogeneous cells with less delay. In the proposed approach, all the secondary peers have been further divided into several secondary peer groups based on credit value. The credit of all the secondary peers will be assigned based on their probability of successful participation in consensus. The secondary nodes will summarize all their results to return to the local service centre (LSC). Finally, LSC will identify the trusted and malicious peers by confirming the consensus adaptively by integrating the RLAC-FNN. The performance of the proposed method has analyzed by implementing it in Python platform and compared with existing approaches. The simulation outcomes showed that the proposed method could efficiently reduce the authentication frequency, handover delay, consensus delay, etc., than existing approaches.

你可以尝试使用大模型来生成摘要 立即生成

【Keywords】Local service centre; Ultra-dense heterogeneous networks; Blockchain-enabled authentication handover; APs group; And actor-critic learning

【发表时间】2023

【收录时间】2023-06-20

【文献类型】 实验仿真

【DOI】 10.1007/s11276-023-03371-z

【Author】 Bordel, Borja Alcarria, Ramon Robles, Tomas

【Source】WIRELESS NETWORKS CCF-C

【影响因子】2.701

【主题类别】

区块链应用-实体经济-环境领域

【Abstract】Ambient Intelligence deployments are very vulnerable to Cyber-Physical attacks. In these attacking strategies, intruders try to manipulate the behavior of the global system by affecting some key elements within the deployment. Typically, attackers inject false information, integrate malicious devices within the deployment, or infect communications among sensor nodes, among other possibilities. To protect Ambient Intelligence deployments against these attacks, complex data analysis algorithms are usually employed in the cloud to remove anomalous information from historical series. However, this approach presents two main problems. First, it requires all Ambient Intelligence systems to be networked and connected to the cloud. But most new applications for Ambient Intelligence are supported by isolated systems. And second, they are computationally heavy and not compatible with new decentralized architectures. Therefore, in this paper we propose a new decentralized security solution, based on a Blockchain ledger, to protect isolated Ambient Intelligence deployments. In this ledger, new sensing data are considered transactions that must be validated by edge managers, which operate a Blockchain network. This validation is based on reputation metrics evaluated by sensor nodes using historical network data and identity parameters. Through information theory, the coherence of all transactions with the behavior of the historical deployment is also analyzed and considered in the validation algorithm. The relevance of edge managers in the Blockchain network is also weighted considering the knowledge they have about the deployment. An experimental validation, supported by simulation tools and scenarios, is also described. Results show that up to 93% of Cyber-Physical attacks are correctly detected and stopped, with a maximum delay of 37 s.

你可以尝试使用大模型来生成摘要 立即生成

【Keywords】Blockchain; Ambient intelligence; Reputation; Information theory; Consensus protocols; Data security

【发表时间】2023

【收录时间】2023-06-20

【文献类型】 理论模型

【DOI】 10.1007/s11276-023-03375-9

【Author】 Chen, Fengmei Zhao, Bin Gao, Yilong Zhang, Wenyin

【Source】JOURNAL OF SUPERCOMPUTING

【影响因子】2.557

【主题类别】

区块链技术-协同技术-身份验证

【Abstract】With the increase in the market share of data trading, the risks such as identity authentication and authority management are increasingly intensified. Aiming at the problems of centralization of identity authentication, dynamic changes of identities, and ambiguity of trading authority in data trading, a two-factor dynamic identity authentication scheme for data trading based on alliance chain (BTDA) is proposed. Firstly, the use of identity certificates is simplified to solve the problems of large calculation and difficult storage. Secondly, a two-factor dynamic authentication strategy is designed, which uses distributed ledger to achieve dynamic identity authentication throughout the data trading. Finally, a simulation experiment is carried out on the proposed scheme. The theoretical comparison and analysis with similar schemes show that the proposed scheme has lower cost, higher authentication efficiency and security, easier authority management, and can be widely used in various fields of data trading scenarios.

你可以尝试使用大模型来生成摘要 立即生成

【Keywords】Two factor; Dynamic identity authentication; Data trading; Alliance chain

【发表时间】2023

【收录时间】2023-06-20

【文献类型】 实验仿真

【DOI】 10.1007/s11227-023-05393-y

【Author】 Umer, Muhammad Sadiq, Saima Alhebshi, Reemah M. Sabir, Maha Farouk Alsubai, Shtwai Al Hejaili, Abdullah Khayyat, Mashael M. Eshmawi, Ala'Abdulmajid Mohamed, Abdullah

【Source】PEERJ COMPUTER SCIENCE

【影响因子】2.411

【主题类别】

区块链应用-实体经济-智能家居

【Abstract】For the past few years, the concept of the smart house has gained popularity. The major challenges concerning a smart home include data security, privacy issues, authentication, secure identification, and automated decision-making of Internet of Things (IoT) devices. Currently, existing home automation systems address either of these challenges, however, home automation that also involves automated decision -making systems and systematic features apart from being reliable and safe is an absolute necessity. The current study proposes a deep learning-driven smart home system that integrates a Convolutional neural network (CNN) for automated decision-making such as classifying the device as "ON" and "OFF" based on its utilization at home. Additionally, to provide a decentralized, secure, and reliable mechanism to assure the authentication and identification of the IoT devices we integrated the emerging blockchain technology into this study. The proposed system is fundamentally comprised of a variety of sensors, a 5 V relay circuit, and Raspberry Pi which operates as a server and maintains the database of each device being used. Moreover, an android application is developed which communicates with the Raspberry Pi interface using the Apache server and HTTP web interface. The practicality of the proposed system for home automation is tested and evaluated in the lab and in real-time to ensure its efficacy. The current study also assures that the technology and hardware utilized in the proposed smart house system are inexpensive, widely available, and scalable. Furthermore, the need for a more comprehensive security and privacy model to be incorporated into the design phase of smart homes is highlighted by a discussion of the risks analysis' implications including cyber threats, hardware security, and cyber attacks. The experimental results emphasize the significance of the proposed system and validate its usability in the real world.

你可以尝试使用大模型来生成摘要 立即生成

【Keywords】Internet of things; Cyber threats; Hardware security; Sensors; Home automation; Cyber attacks

【发表时间】2023

【收录时间】2023-06-20

【文献类型】 理论模型

【DOI】 10.7717/peerj-cs.1332

【Author】 Huang, Lingling Zhao, Chengqiang Chen, Shijie Zeng, Liujing

【Source】ASLIB JOURNAL OF INFORMATION MANAGEMENT

【影响因子】1.935

【主题类别】

区块链应用-实体经济-法律领域

【Abstract】PurposeTechnical advantages embraced by blockchain, such as distributed ledger, P2P networks, consensus mechanisms and smart contracts, are highly compatible with addressing the security issues of transferring and storing judicial documents and obtaining the feedback and evaluation of judicial translation services in cases with foreign elements. Therefore, based on this, a consortium blockchain-based model for supervising the overall process of judicial translation services in cases with foreign elements is proposed.Design/methodology/approachSome judicial documents are required to be translated when there are language barriers in cases with foreign elements. The purpose of this paper is expected to address security issues, which is ignored, in the process of translating judicial documents.FindingsThe experimental results show that the model constructed in this paper can effectively guarantee the security and privacy of transferring and storing translated judicial documents in cases with foreign elements, and realize the credibility and traceability of feedbacks and evaluations of judicial translation services. In addition, the underlying network communications is stable and the speed for processing data can meet the requirements of practical application.Originality/valueThe research in this paper provides an innovative scheme for judicial translation services in cases with foreign elements. The model constructed is conducive to protecting the security of the transfer and storage of judicial documents and improving the efficiency and modernization ability of hearing cases with foreign elements.

你可以尝试使用大模型来生成摘要 立即生成

【Keywords】Blockchain; Cases with foreign elements; Judicial translation services; Security

【发表时间】2023

【收录时间】2023-06-20

【文献类型】 理论模型

【DOI】 10.1108/AJIM-11-2022-0485

【Author】 You, Xuan Zhou, Changsong Chen, Zeng Han, Rui Gu, Yu Sun, Guozi

【Source】JOURNAL OF SIGNAL PROCESSING SYSTEMS FOR SIGNAL IMAGE AND VIDEO TECHNOLOGY

【影响因子】1.813

【主题类别】

区块链技术-核心技术-存储策略

【Abstract】With the development of the big data era, the amount of data has entered an explosive growth phase. Limited by the constraints of cost, efficiency, and security of self-built storage systems, enterprises are forced to outsource files to cloud storage systems. However, the lack of file security and auditability in cloud storage systems continues to threaten the security of outsourced files. This paper designs and implements a large file security outsourcing and sharing method based on blockchain (BFSOut). It uses Hyperledger Fabric and Interplanetary File System (IPFS) as the underlying storage engine, which solves the problem of cloud storage security issues. In order to ensure the security of outsource files, the client-side offline encryption and decryption is used. Furthermore, a dynamic hybrid encryption scheme is adopted, making the overall encryption effect more efficient. Meanwhile, BFSOut effectively reduces the time consumption of large file encryption and decryption by 20%-30% through the parallel block encryption and decryption model. Experimental performance and security analysis show that the method has good performance and safety.

你可以尝试使用大模型来生成摘要 立即生成

【Keywords】File security outsourcing; Blockchain; Hybrid encryption; Parallel encryption

【发表时间】2023

【收录时间】2023-06-20

【文献类型】 实验仿真

【DOI】 10.1007/s11265-023-01873-9

【Author】 Luong, Hai Thanh

【Source】SECURITY JOURNAL

【影响因子】1.701

【主题类别】

区块链治理-法律治理-暗网

【Abstract】After the Silk Road closure, many studies started focusing on the trend and patterns of darknet-related crimes in the 2010s. This first study combined a systematic literature review and bibliometric analysis in the field. This study clarifies 49 articles in criminology and penology among 1150 publications relating to the darknet on the Web of Science database to review and analyze the research evolutions of this topic in the last decade. The main findings point out (1) almost all leading authors with their most influential papers came from the Global South with predominant contributions; (2) unbalancing publications between regional scholars and their institutions and countries although the darknet-related criminals occurred and operated without border; and (3) some specialized themes have identified to call further extensive research such as policing interventions in the darknet and flows of the cryptocurrency in cryptomarkets, among others.

你可以尝试使用大模型来生成摘要 立即生成

【Keywords】Darknet; Criminology; Policing; Cryptocurrency; Network; Silk road

【发表时间】2023

【收录时间】2023-06-20

【文献类型】 综述

【DOI】 10.1057/s41284-023-00383-4

【Author】 Li, Jianbin Li, Jifang Xie, Chunlei Liang, Yousheng Qu, Ketong Cheng, Long Zhao, Zhiming

【Source】JOURNAL OF CIRCUITS SYSTEMS AND COMPUTERS

【影响因子】1.278

【主题类别】

区块链技术-协同技术-知识图谱

【Abstract】The increasing sophistication of cyberattacks on blockchain systems has significantly disrupted security experts from gaining immediate insight into the security situation. The Cybersecurity Knowledge Graph (CKG) currently provides a novel technical solution for blockchain system situational awareness by integrating massive fragmented Cyber Threat Intelligence (CTI) about blockchain technology. However, the existing literature does not provide a solution for building CKG appropriate for blockchain systems. Therefore, designing a method to construct a CKG for blockchain systems by efficiently extracting information from the CTI is mandatory. This paper proposes PipCKG-BS, a pipeline-based approach that builds CKG for blockchain systems. The PipCKG-BS incorporates contextual features and Pre-trained Language Models (PLMs) to improve the performance of the information extraction process. Precisely, we develop the Named Entity Recognition (NER) and Relation Extraction (RE) models for cybersecurity text in PipCKG-BS. In the NER model, we apply the prompt-based learning paradigm to cybersecurity text by constructing prompt templates. In the RE model, we employ external features and prior knowledge of sentences to improve entity relationship extraction accuracy. Several experimental results demonstrate that PipCKG-BS is better than advanced methods in extracting CTI information and is an appealing solution to build high-quality CKG for blockchain systems.

你可以尝试使用大模型来生成摘要 立即生成

【Keywords】Cybersecurity knowledge graph; cyber threat intelligence; relationship extraction; named entity recognition

【发表时间】2023

【收录时间】2023-06-20

【文献类型】 实验仿真

【DOI】 10.1142/S0218126623502742