【Author】 Masteika, Saulius Rebzdys, Eimantas Driaunys, K. estutis Sapkauskiene, Alfreda Macerinskiene, Aida Krampas, Evaldas

【Source】INTERNATIONAL JOURNAL OF INFORMATION MANAGEMENT

【影响因子】18.958

【主题类别】

区块链治理-市场治理-数字货币安全

【Abstract】This research examines vulnerabilities and potential attacks using Bitcoin payment systems at physical retail locations. It also lays a theoretical and practical foundation for effective countermeasures that ensure the integrity of decentralized transactions and bolster the confidence of both merchants and customers. The study focuses on potential double-spend attacks, particularly in the context of instant payments made via non-custodial crypto wallets. It also evaluates alternatives for instant crypto payments that use alternative coins and secondlayer blockchain solutions. Research has indicated that Eclipse, Sybil, Majority, Race, and Finney attacks carry a relatively low risk, especially when payment amounts are limited. The paper identifies Replace-By-Fee attacks as the most significant threat and presents a set of countermeasures. These findings are of great importance to cryptocurrency experts, payment tech researchers, retail enterprises, and stakeholders using noncustodial wallets while exploring decentralized blockchain aspects.

你可以尝试使用大模型来生成摘要 立即生成

【Keywords】Bitcoin; Instant payments; Zero-confirmation; Lightning network; Non-custodial wallets

【发表时间】2024

【收录时间】2024-09-20

【文献类型】 案例研究

【DOI】 10.1016/j.ijinfomgt.2023.102727

【Author】 Kayani, Umar Ullah, Mirzat Aysan, Ahmet Faruk Nazir, Sidra Frempong, Josephine

【Source】TECHNOLOGICAL FORECASTING AND SOCIAL CHANGE

【影响因子】10.884

【主题类别】

区块链治理-市场治理-市场分析

【Abstract】This study delves into an exploration of quantile connectedness across the domains of digital and traditional financial assets with the renewable energy prices index. The daily frequency dataset, spanning from January 02, 2018, to December 04, 2023, encapsulates diverse economic crises. Our inquiry elucidates distinctive patterns by employing empirical analyses utilizing quantile connectedness and Time-Varying Parameter Vector Autoregressive (TVP-VAR) methodologies. In this context, DeFi assets (Chain-link) emerge as the primary recipient of information shocks, while Bitcoin distinguishes itself as the preeminent transmitter of such shocks within the network. Notably, digital assets manifest heightened volatility in contrast to traditional and energy indices. Furthermore, our findings underscore that the gaming industry, specifically focusing on Non-Fungible Tokens (NFT), presents itself as the most fitting asset for portfolio inclusion. This assertion gains credence from its comparatively lower degree of connectedness with other underlying assets. These findings have significant implications for investors and portfolio managers, furnishing valuable insights into the dynamics of asset interdependencies. Consequently, this aids in cultivating a more discerning approach to investment decisionmaking.

你可以尝试使用大模型来生成摘要 立即生成

【Keywords】Quantile connectedness; Quantile DeFi; NFT; Financial assets; Renewable energy; Portfolio diversification

【发表时间】2024

【收录时间】2024-09-20

【文献类型】 观点阐述

【DOI】 10.1016/j.techfore.2024.123635

【Author】 Qahtan, Sarah Mourad, Nahia Ibrahim, Hassan A. Zaidan, Aws Alaa Bahaa, Bilal Deveci, Muhammet Ding, Weiping Pamucar, Dragan Pedrycz, Witold Shamini, Saraswathy

【Source】EXPERT SYSTEMS WITH APPLICATIONS CCF-C

【影响因子】8.665

【主题类别】

区块链技术-协同技术-6G

【Abstract】The use of blockchain technology in sixth-generation (6G) networks promises substantial improvements in security, privacy, efficiency, and cost-effectiveness. Extensive research has explored various 6G frameworks incorporating blockchain, revealing how different blockchain features impact technical requirements. Thus, selecting and modelling these frameworks are pivotal. A research gap exists as no standard model exists for these frameworks based on blockchain features, presenting a multi-attribute decision-making challenge due to feature diversity, uncertain importance, and data variability. This study introduces an innovative intelligent approach, incorporating fuzzy weighted zero inconsistency (FWZIC) based on the interrelationship process under a normal wiggly hesitant fuzzy set (NWHFS) environment named NWHFS-FWZIC method and ranking of alternatives through functional mapping of criterion sub-intervals into a single interval (RAFSI) method. The decision matrix for the study is built by intersecting 10 6G technical requirements with 7 blockchain evaluation features of 6G frameworks. The proposed intelligent approach in NWHFS-FWZIC is further developed to ascertain the importance level of the multiple blockchain features. These data are used in RAFSI. Results revealed that the decentralization feature (Dec) was assigned the highest weight value (0.4653) according to NWHFS-FWZIC, indicating its important role in modelling 6G frameworks. The non-repudiation feature (NR) was assigned a weight value of 0.0156, indicating its moderate importance in modelling 6G frameworks. ERLLC/eURLLC achieved the highest score of 0.7600, reflecting strong performance across most features, particularly in NR, Dec, and Smart Contracts (SCs). LDHMC followed closely with a score of 0.7433, demonstrating balanced performance with notable strengths in Immutability (Imm) and Trust-building (TB). The FeMBB and umMTC models also performed well, with scores of 0.7106 and 0.7223 respectively, indicating reliability and efficiency in multiple evaluation features. while ELPC and HATC were the least favoured frameworks. The robustness of the proposed method is assessed through sensitivity analyses, systematic test, and performance comparative with state of art study.

你可以尝试使用大模型来生成摘要 立即生成

【Keywords】Blockchain technology; FWZIC; Multi-criteria decision-making; Normal wiggly hesitant fuzzy set; RAFSI; 6G

【发表时间】2025

【收录时间】2024-09-20

【文献类型】 理论模型

【DOI】 10.1016/j.eswa.2024.125304

【Author】 Tomar, Ashish Tripathi, Sachin

【Source】IEEE TRANSACTIONS ON MOBILE COMPUTING CCF-A

【影响因子】6.075

【主题类别】

区块链应用-实体经济-车联网

【Abstract】The increasing number of vehicles has resulted in a tremendous growth of data in vehicular communications. Cloud-based models are inefficient for handling this large data due to high latency and bandwidth requirements. To address this, fog computing-based vehicular network models have been proposed for low latency and immediate responses. However, securing data transfer between fog servers and vehicles on public channels is essential to prevent malicious attacks. Existing authenticated key agreement schemes provide security but often incur high computational costs and vulnerability to attacks. Thus, this paper proposes a blockchain-based authenticated key agreement scheme for the fog computing-enabled vehicular network. The proposed scheme integrates blockchain into fog-based Vehicular Ad-hoc Network (VANET), where fog servers and the cloud servers serve as blockchain nodes for seamless re-authentication of a moving vehicle. For secure communication, the proposed scheme uses the Chebyshev polynomial to achieve low computational cost and establishes a common session key between cloud server, fog server, and vehicle. The formal security proof of the proposed scheme is carried out using Real-Or-Random (ROR) model. Finally, the Hyperledger Fabric and cryptographic libraries have been used for the experimental analysis to demonstrate the proposed scheme's communication and computational efficiency.

你可以尝试使用大模型来生成摘要 立即生成

【Keywords】Authentication; Servers; Security; Protocols; Cloud computing; Blockchain; chebyshev chaotic maps; fog computing; mutual authentication; vehicular ad hoc networks (VANET); mutual authentication; vehicular ad hoc networks (VANET)

【发表时间】2024

【收录时间】2024-09-20

【文献类型】 实验仿真

【DOI】 10.1109/TMC.2024.3357599

【Author】 Tang, Ming Peng, Fu Wong, Vincent W. S.

【Source】IEEE TRANSACTIONS ON MOBILE COMPUTING CCF-A

【影响因子】6.075

【主题类别】

区块链技术-协同技术-联邦学习

【Abstract】In cross-silo federated learning (FL), organizations cooperatively train a global model with their local datasets. However, some organizations may act as free riders such that they only contribute a small amount of resources but can obtain a high-accuracy global model. Meanwhile, some organizations can be business competitors, and they do not trust each other or any third-party entity. In this work, our goal is to design a framework that motivates efficient cooperation among organizations without the coordination of a central entity. To this end, we propose a blockchain-empowered incentive mechanism framework for cross-silo FL. Under this incentive mechanism framework, we develop a distributed algorithm that enables organizations to achieve social efficiency, individual rationality, and budget balance without private information of the organizations. Our proposed algorithm has a proven convergence guarantee and empirically achieves a higher convergence rate than a benchmark method. Moreover, we propose a transaction minimization algorithm to reduce the number of transactions made among organizations in the blockchain. This algorithm is proven to achieve a performance no worse than twice the minimum value. The experimental results in a testbed show that our proposed framework enables organizations to achieve social efficiency within a relatively short iterative process.

你可以尝试使用大模型来生成摘要 立即生成

【Keywords】Organizations; Training; Costs; Load modeling; Smart contracts; Servers; Blockchain; federated learning; game theory; incentive mechanism; resource allocation; resource allocation

【发表时间】2024

【收录时间】2024-09-20

【文献类型】 实验仿真

【DOI】 10.1109/TMC.2024.3361089

【Author】 Wu, Haiqin Dudder, Boris Jiang, Shunrong Wang, Liangmin

【Source】IEEE TRANSACTIONS ON MOBILE COMPUTING CCF-A

【影响因子】6.075

【主题类别】

区块链应用-实体经济-众包领域

【Abstract】Privacy-aware task allocation/matching has been an active research focus in crowdsourcing. However, existing studies focus on an honest-but-curious assumption and a single-attribute matching model. There is a lack of adequate attention paid to scheme designs against malicious behaviors and supporting user-side personalized task matching over multiple attributes. A few recent works employ blockchain and cryptographic techniques to decentralize the matching procedure with verifiable and privacy-preserving on-chain executions. However, they still bear expensive on-chain overhead. In this paper, we propose VP2-Match, a blockchain-assisted (publicly) verifiable privacy-aware crowdsourcing task matching scheme with personalization. VP2-Match extends symmetric hidden vector encryption for user-side expressive matching without compromising their privacy. It avoids costly on-chain matching by letting the blockchain only store evidence/proofs for public verifiability of the matching correctness and for enforcing fair interactions against misbehaviors. Specifically, we construct extended attribute sets and solve matching verification by an algorithmic reduction into subset verification with an accumulator for proof generation. Formal security proof and extensive comparison experiments on Ethereum demonstrate the provable security and better performance of VP2-Match, respectively.

你可以尝试使用大模型来生成摘要 立即生成

【Keywords】Task analysis; Vectors; Privacy; Cryptography; Encryption; Blockchain; crowdsourcing; personalized task allocation; privacy protection; public verifiability; privacy protection; public verifiability

【发表时间】2024

【收录时间】2024-09-20

【文献类型】 实证数据

【DOI】 10.1109/TMC.2024.3369085

【Author】 Zafir, Ehsanul Islam Akter, Afifa Islam, M. N. Hasib, Shahid A. Islam, Touhid Sarker, Subrata K. Muyeen, S. M.

【Source】INTERNET OF THINGS

【影响因子】5.711

【主题类别】

区块链应用-实体经济-物联网

【Abstract】The Internet of Robotic Things (IoRT) integrates robots and autonomous devices, transforming industries such as manufacturing, healthcare, and transportation. However, security vulnerabilities in IoRT systems pose significant challenges to data privacy and system integrity. To address these issues, encryption is essential for protecting sensitive data transmitted between devices. By converting data into ciphertext, encryption ensures confidentiality and integrity, reducing the risk of unauthorized access and data breaches. Blockchain technology also enhances IoRT security by offering decentralized, tamper-proof data storage solutions. By offering comprehensive insights, practical recommendations, and future directions, this paper aims to contribute to the advancement of knowledge and practice in securing interconnected robotic systems, thereby ensuring the integrity and confidentiality of data exchanged within IoRT ecosystems. Through a thorough examination of encryption requisites, scopes, and current implementations in IoRT, this paper provides valuable insights for researchers, engineers, and policymakers involved in IoRT security efforts. By integrating encryption and blockchain technologies into IoRT systems, stakeholders can foster a secure and dependable environment, effectively manage risks, bolster user confidence, and expedite the widespread adoption of IoRT across diverse sectors. The findings of this study underscore the critical role of encryption and blockchain technology in IoRT security enhancement and highlight potential avenues for further exploration and innovation. Furthermore, this paper suggests future research areas, such as threat intelligence and analytics, security by design, multi-factor authentication, and AI for threat detection. These recommendations support ongoing innovation in securing the evolving IoRT landscape.

你可以尝试使用大模型来生成摘要 立即生成

【Keywords】IoRT; Encryption; Cryptography; Cyber security; Security algorithm; Robotics; IoT

【发表时间】2024

【收录时间】2024-09-20

【文献类型】 综述

【DOI】 10.1016/j.iot.2024.101357

【Author】 Ryu, Hyun-Sun

【Source】INTERNATIONAL JOURNAL OF BANK MARKETING

【影响因子】5.083

【主题类别】

区块链治理-市场治理-行为分析

【Abstract】PurposeAlongside its remarkable growth, problematic Bitcoin investment (BI) behavior and its associated negative consequences have become prevalent, and only a few studies have examined it. Therefore, this study aims to examine problematic BI behavior by investigating its specific antecedents and consequences and identifying which antecedents were more influential in it. In addition, we also examine the role of financial literacy on the relationship between the antecedents and problematic BI behavior.Design/methodology/approachWe collected survey data from 413 investors with Bitcoin investment experience in 2018, when a Bitcoin frenzy occurred. The partial least squares method was used to test the proposed research model.FindingsThe results show that prudent, negative urgency, overexpectation and sensation seeking are positively associated with problematic BI behavior, while restraint is negatively associated. Problematic BI behavior is negatively related to investor well-being. Our findings also indicate that both objective and subjective financial literacy moderate the relationship between the antecedents and problematic BI behavior. Four types of investors in terms of their objective and subjective Bitcoin knowledge show different patterns in the relationship between the antecedents and problematic BI behavior.Originality/valueThis study offers insights for researchers by providing a deeper understanding of the contextual antecedents of problematic BI behavior and the role of financial literacy in it. This study provides detailed implications for financial institutions, policymakers, and regulators to guide rational Bitcoin investment behaviors.

你可以尝试使用大模型来生成摘要 立即生成

【Keywords】Bitcoin; Problematic investment; Behavioral control; Emotional preoccupation; Financial literacy; Investment outcome

【发表时间】2024

【收录时间】2024-09-20

【文献类型】 实证数据

【DOI】 10.1108/IJBM-01-2024-0018

【Author】 Alsamhi, Saeed Hamood Hawbani, Ammar Sahal, Radhya Srivastava, Sumit Kumar, Santosh Zhao, Liang Al-qaness, Mohammed A. A. Hassan, Jahan Guizani, Mohsen Curry, Edward

【Source】AD HOC NETWORKS CCF-C

【影响因子】4.816

【主题类别】

区块链应用-实体经济-工业领域

【Abstract】The dramatic recent increase of the smart Internet of Everything (IoE) in Industry 4.0 has significantly increased energy consumption, carbon emissions, and global warming. IoE applications in Industry 4.0 face many challenges, including energy efficiency, heterogeneity, security, interoperability, and centralization. Therefore, Industry 4.0 in Beyond the Sixth-Generation (6G) networks demands moving to sustainable, green IoE and identifying efficient and emerging technologies to overcome sustainability challenges. Many advanced technologies and strategies efficiently solve issues by enhancing connectivity, interoperability, security, decentralization, and reliability. Greening IoE is a promising approach that focuses on improving energy efficiency, providing a high Quality of Service (QoS), and reducing carbon emissions to enhance the quality of life at a low cost. This survey provides a comprehensive overview of how advanced technologies can contribute to green IoE in the 6G network of Industry 4.0 applications. This survey provides a comprehensive overview of advanced technologies, including Blockchain, Digital Twins (DTs), Unmanned Aerial Vehicles (UAVs, a.k.a. drones), and Machine Learning (ML), to improve connectivity, QoS, and energy efficiency for green IoE in 6G networks. We evaluate the capability of each technology in greening IoE in Industry 4.0 applications and analyse the challenges and opportunities to make IoE greener using the discussed technologies.

你可以尝试使用大模型来生成摘要 立即生成

【Keywords】Green IoE; Industry 4.0; 6G; Energy efficiency; Connectivity; Sustainability

【发表时间】2024

【收录时间】2024-09-20

【文献类型】 综述

【DOI】 10.1016/j.adhoc.2024.103610

【Author】 Wijethilaka, Shalitha Yadav, Awaneesh Kumar Braeken, An Liyanage, Madhusanka

【Source】IEEE TRANSACTIONS ON NETWORK AND SERVICE MANAGEMENT CCF-C

【影响因子】4.758

【主题类别】

区块链应用-实体经济-通信领域

【Abstract】The rapid evolution of heterogeneous applications signifies the requirement for network slicing to cater to diverse network requirements. Network Functions (NFs), which are the essential elements of network slices, are required to communicate with each other securely to facilitate network services. Certificates are the established method to authenticate each other. However, dynamic certificate management while allowing NFs to communicate in a multi-operator environment is arduous. Also, sharing NFs between network slices originates authorization-related security challenges such as unauthorized service utilization, deceptive Denial of Service attacks, and data leakages from network slices. In this paper, we develop a novel framework to address the security challenges related to authentication and authorization in 5G network slicing systems. A blockchain-based multi-party distributed certificate management framework with secure communication protocols is developed using elliptic curve cryptography to facilitate certificate services for multi-operator environments. Also, we propose a blockchain-based NF authorization framework to mitigate the security vulnerabilities in NF sharing between network slices. We implement the proposed framework using Hyperledger Fabric blockchain with Java chain codes and perform comprehensive experiments to show the significance of our framework. The Ability to mitigate the single point of failure with respect to state-of-the-art, including traditional certificate authorities and blockchain-based certificate authorities, time analysis for certificate generation, and the potential to eliminate the mentioned authorization attacks are some of the experiments conducted. Also, we have shown that our framework is secure using informal and formal (using Real-Or-Random (ROR) logic and Scyther Validation tool) security verification mechanisms.

你可以尝试使用大模型来生成摘要 立即生成

【Keywords】Noise measurement; Security; Blockchains; Authorization; Network slicing; Authentication; 5G mobile communication; 5G; network slicing; blockchain; authentication; authorization; security; certificate

【发表时间】2024

【收录时间】2024-09-20

【文献类型】 理论模型

【DOI】 10.1109/TNSM.2024.3416418

【Author】 Agrawal, Shraddha Tiwari, Sanjiv Kumar Singh, Ritesh Kumar

【Source】ENVIRONMENT DEVELOPMENT AND SUSTAINABILITY

【影响因子】4.080

【主题类别】

区块链应用-实体经济-供应链

【Abstract】The revolutionary impact of Blockchain Technology is undeniable, transforming industries globally with its ability to reduce costs, shorten processing times, and eliminate intermediaries. It is reshaping industries by establishing trust and transparency through its immutable and traceable nature, leading to a paradigm shift in supply chain management operations. So, driven by the need to eliminate inefficiencies, this technology is gaining strong traction in the agricultural and food industries to streamline its operation. However, a comprehensive understanding of the factors enabling Blockchain Technology is essential for its effective implementation in this industry. The prime focus of the present work is to identify and prioritize Blockchain Technology enablers that can mitigate the challenges associated with the agriculture and food industries. In this regard, this study presents a novel Intuitionistic Fuzzy Grey Relational Analysis (IF-GRA) method for assessing the enablers of Blockchain Technology. The study identified Traceability as the most vital factor with a grey relational grade value of 0.987, followed by Smart Contracts (0.9302), Transparency (0.9238), and Real-Time Connectivity (0.8037). Further, this research also provides essential insights for agricultural and food industries contemplating the integration of Blockchain Technology.

你可以尝试使用大模型来生成摘要 立即生成

【Keywords】Blockchain technology; Agriculture and food industry supply chain; Intuitionistic fuzzy grey relational analysis (IF-GRA)

【发表时间】2024

【收录时间】2024-09-20

【文献类型】 实证数据

【DOI】 10.1007/s10668-024-05315-9

【Author】 Wu, Meng Xu, Feng Subramaniam, Geetha Li, Zeyu Chen, Liyun Zhu, Wenjuan

【Source】IEEE ACCESS

【影响因子】3.476

【主题类别】

区块链应用-实体经济-医疗领域

【Abstract】Hematopoietic stem cell transplantation (HSCT) is a crucial treatment option for hematological disorders. This study aims to design and develop a blockchain-based system tailored explicitly for HSCT typing and evaluate its performance and capabilities. The system, built on Hyperledger Fabric 2.4.6 and integrated with LevelDB and MySQL databases, implements features such as data on-chaining, access control, information retrieval, and matching through chaincode. It ensures accurate and efficient human leukocyte antigen (HLA) typing while protecting patient and hospital data security. Tests demonstrate the system's ability to safeguard data security and reliability effectively. Performance metrics, including block size, CPU utilization, network throughput, and response latency, were evaluated on Ubuntu 20.04.2 operating systems using VMware Workstation 16 Pro and Docker containerization. By leveraging blockchain's traceability and immutability, the system achieves data security, reliability, and verifiability, enabling faster and more accurate typing and improved healthcare efficiency. This innovative approach optimizes user experience, maintains data integrity, and ensures privacy. Future integration with existing databases could enable secure data sharing among healthcare institutions, allowing rapid verification of data ownership and unified authentication. This study contributes a significant advancement in hematologic disease treatment and research, offering practical implications for improving HSCT processes.

你可以尝试使用大模型来生成摘要 立即生成

【Keywords】Blockchain technology; hematopoietic stem cell transplantation (HSCT); hospital information system; human leukocyte antigen (HLA) typing; Hyperledger Fabric

【发表时间】2024

【收录时间】2024-09-20

【文献类型】 实验仿真

【DOI】 10.1109/ACCESS.2024.3434953

【Author】 Anbaee Farimani, Saeede Jahan, Majid Vafaei Milani Fard, Amin

【Source】IEEE ACCESS

【影响因子】3.476

【主题类别】

区块链治理-市场治理-价格预测

【Abstract】Investors' trading behavior is influenced by a multimode of information sources such as technical analysis, news dissemination, and sentiment, which results in the non-stationary behavior of financial time series. With advancements in deep learning, studies considering temporal relationships in each data mode and applying heterogeneous data fusion techniques for market prediction are increasing. While net price change prediction is helpful for investors, most previous deep learning models only predict the up/down trend of price as the non-stationary behavior of price time series influences the regression performance. In this work, we present an adaptive model for price regression, which learns interdependencies between the distribution of multimode data and the amount of price change around an average price for snapshots of systems. We use news content, the mood in specialized newsgroups, and technical indicators for data representation. Different news topics, also known as modalities, can be absorbed by investors with different diffusion speeds; hence we use a concept-based news representation method that reflects news topics in a news vector. Also, our model considers the positive/negative mood in specialized newsgroups and technical indicators. To capture complex temporal characteristics in the distribution of economic concepts in the news sequence, we use a recurrent convolutional neural network and other recurrent layers to perceive changes in technical indicators and mood in specialized newsgroups. In the fusion layer, our model learns to normalize data points based on their estimated distribution and the importance weight of each data mode to handle multimodality challenges. To overcome the non-stationary behavior of price, we let the network learn how to drift the predicted values around the average price of that packet. Our experiments demonstrate a significant 40.11% error reduction compared to the baselines. We also discuss the adaptability, and price prediction capability of our proposed approach.

你可以尝试使用大模型来生成摘要 立即生成

【Keywords】Feature extraction; Predictive models; Adaptation models; Mood; Vectors; Time series analysis; Sentiment analysis; Market research; Stock markets; Investment; Adaptive fusion strategy; cryptocurrency market; financial sentiment analysis; market prediction; news document representation

【发表时间】2024

【收录时间】2024-09-20

【文献类型】 实验仿真

【DOI】 10.1109/ACCESS.2024.3441029

【Author】 Khoury, David Haddad, Samir Sondi, Patrick Abou Haidar, Gaby Semaan, David Sayah, Jinane

【Source】IEEE ACCESS

【影响因子】3.476

【主题类别】

区块链应用-实体经济-物联网

【Abstract】Recently, the focus on the Internet of Things (IoT) has rocketed in parallel with the evolution of mobile fifth-generation (5G) networks. To fully utilize IoT, which wirelessly connects billions of devices, a 5G network is essential. However, the provision of user's certificates exposes the network to serious security threats. The LightCert4IoT leverages the advantages of EDGE nodes with blockchain technology and smart contracts to address the existing challenges of PKI (Public Key Infrastructure) certificates in IoT devices, which neatly achieves certificate issuance, update, and revocation more securely and efficiently. An end-user issues a self-signed certificate and lets Local Registration Authorities (LRAs)/EDGE nodes to verify and validate the binding identity signed certificate of the users through a blockchain such as Ethereum. This work analyzes the performance of LightCert4IoT in IoT devices by utilizing the Cooja-Contiki simulator. The results show reduced energy consumption and memory size when compared to the conventional X509 certificate. In conclusion, the LightCert4IoT meets the requirements of major IoT device constraints. The paper also addresses the security threats with the widespread use of IoT devices and analyses the adversary on security level from the authentication based on hardware token and blockchain and deploying firewall to protect servers against malicious attacks like DDOS. Scalability, resource limitations, and privacy concerns are analyzed as IoT devices handle sensitive information, and the transparent and immutable nature of blockchain can raise data protection. Analysis of Network partitioning challenge and communication overhead

你可以尝试使用大模型来生成摘要 立即生成

【Keywords】Internet of Things; Blockchains; Security; Smart contracts; Object recognition; Authentication; Public key; Certification; 5G mobile communication; Certificate; blockchain; public key infrastructure; authentication; IoT-5G; simulation

【发表时间】2024

【收录时间】2024-09-20

【文献类型】 案例研究

【DOI】 10.1109/ACCESS.2024.3451134

【Author】 Choi, Insu Kim, Woo Chang

【Source】INTERNATIONAL REVIEW OF ECONOMICS & FINANCE

【影响因子】3.399

【主题类别】

区块链治理-市场治理-价值识别

【Abstract】This study explores the complex interdependencies among five major financial assets-S&P 500, Bitcoin, Crude Oil, Gold, and USD/EUR-from April 2015 to September 2022, emphasizing the importance of understanding global financial dynamics for robust financial management. We quantitatively analyze daily causal relationships using conditional transfer entropy, a method that surpasses traditional correlation analyses. By incorporating the effective federal funds rate into our models, we enhance predictive accuracy and account for monetary policy impacts, ensuring our findings are relevant to current economic conditions. Our results reveal significant causal networks, providing key insights into asset interdependencies that support advanced hedging strategies and effective diversification. This research improves prediction models through the innovative use of network-based features and offers practical strategies for managing multinational financial assets, with relevance across various economic scenarios.

你可以尝试使用大模型来生成摘要 立即生成

【Keywords】Financial market analysis; Information flow; Conditional transfer entropy; Financial index; Network analysis; Explainable framework in finance

【发表时间】2024

【收录时间】2024-09-20

【文献类型】 案例研究

【DOI】 10.1016/j.iref.2024.103562

【Author】 Tian, Shiyu Jiang, Wenbao

【Source】APPLIED SCIENCES-BASEL

【影响因子】2.838

【主题类别】

区块链应用-实体经济-农业领域

【Abstract】With the rapid development of global information technology, smart agriculture has gradually become an important force to promote agricultural modernisation. Taking Yangcheng Lake hairy crabs as the research object, this paper constructs a full-chain traceability process for hairy crabs integrating blockchain and Internet of Things technology in response to the demand for the enhancement of its brand value and market competitiveness. The model covers all aspects of breeding, processing, and transport to sales; realises end-to-end transparent regulation; effectively guarantees the authenticity and non-tamperability of information; and enhances consumers' trust in the brand. At the technical level, this paper designs the ECMI (Enhanced Cuckoo Merkle Index) model, optimises the data storage and retrieval mechanism, and experimentally verifies the advantages of cuckoo filters over traditional Bloom filters in reducing false positives and improving query efficiency. This paper not only provides an efficient and safe traceability solution for the hairy crab industry in Yangcheng Lake but also provides technical support and practical cases for the further application of blockchain technology in smart agriculture, which is of great value for the realisation of the national rural revitalisation strategy.

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【Keywords】blockchain technology; traceability process; bloom filter; cuckoo filter; Yangcheng lake hairy crab

【发表时间】2024

【收录时间】2024-09-20

【文献类型】 理论模型

【DOI】 10.3390/app14178027