【影响因子】10.517
【主题类别】
区块链应用-实体经济-建筑领域
区块链技术-核心技术-零知识证明
【Abstract】Effective management of near-miss data is essential for proactive safety practices in construction. Traditional reporting and management methods face challenges such as data loss, susceptibility to manipulation, and poor traceability, which undermine their reliability and collaborative efforts. Blockchain technology can enhance data integrity, security, transparency, and reliability in safety data management. However, conventional Layer-1 blockchain systems require third-party verification processes, compromising participant anonymity-crucial for effective near-miss reporting and incur high transaction fees, presenting several practical concerns. To address these issues, this paper developed and tested a zero-knowledge proof and Layer-2 blockchain integrated system for near-miss reporting. This system was validated through a proof-of-concept and hypothetical case study, achieving perfect unlinkability with a degree of anonymity scored at d = 1 and reducing the cost of report submission to USD 0.0011. These advances significantly contribute toward proactive safety management in construction by facilitating safe reporting environments and cost-effective near-miss management.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】Proactive construction safety management; Zero-knowledge proof; Layer-2 blockchain; Near-miss reporting; Decentralized application; Anonymity
【发表时间】2024
【收录时间】2024-10-26
【文献类型】 实验仿真
【Author】 Vu, Nam Ghadge, Abhijeet Bourlakis, Michael
【影响因子】9.018
【主题类别】
区块链应用-实体经济-食品供应链
【Abstract】The food supply chain (FSC) constantly needs to address persistent challenges such as information asymmetry, low transparency, food quality and authenticity, and unnecessary waste. Blockchain is perceived as a promising solution to overcome these FSC challenges. Existing literature captures a conceptual understanding of various aspects of Blockchain for FSC, such as how the technology can enhance transparency, efficiency, and food authenticity. However, a quantitative assessment of the overall impact of Blockchain adoption on the FSC operational performance is still missing. This study combines empirical and analytical approaches to investigate the evident research gap. Under the lens of systems thinking and System Dynamics (SD) modelling perspective, the study collected questionnaire and interview data to develop different FSC models for evaluating the impact of Blockchain on key operational performance metrics. The findings indicated that Blockchain positively affects inventory level and lead time in the immediate term, and cost in the long term. The results also warn that forgoing inventory buffers can come with the cost-of-service level. This study provides quantitative evidence of the positive influence of Blockchain on the FSC. This research contributes by extending the understanding of Blockchain's implications on broader supply chain performance from a systems perspective.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】Blockchain; food supply chain; systems thinking; system dynamics; supply chain performance
【发表时间】2024
【收录时间】2024-10-26
【文献类型】 实证数据
【影响因子】8.235
【主题类别】
区块链治理-市场治理-数字货币
【Abstract】This paper aims to analyze the return-volatility relationship of Bitcoin and Ethereum across different return frequencies and all conditional quantiles of implied volatility, based on a unique 6.5 million observations. We employ the newly constructed Model-Free Implied Volatility (MFIV) of Bitcoin (BitVol) and Ethereum (EthVol) and use an asymmetric Quantile Regression Model (QRM) to capture the intraday asymmetric return-volatility relationship at different quantiles of the distribution of the dependent variable. Our findings show that the estimated coefficient using daily data is significant only at medium- to high-volatility regimes, while the estimated coefficients using high-frequency data are highly significant across all volatility regimes. Moreover, our results indicate that the asymmetry varies across frequencies and quantiles, with weak asymmetric effects at low quantiles and high frequencies, and strong asymmetric effects at high quantiles and low frequencies. This study provides new insight, especially for high-frequency traders.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】Return-volatility; Cryptocurrencies; Asymmetric; Quintile regression; Return frequencies
【发表时间】2024
【收录时间】2024-10-26
【文献类型】 实证数据
CCF-B
【影响因子】8.233
【主题类别】
区块链治理-市场治理-数字资产
区块链技术-协同技术-强化学习
【Abstract】Portfolio optimization has attracted substantial interest within the artificial intelligence community due to its significant impact on financial decision-making, risk management, and market analysis. Reinforcement learning fits well with portfolio optimization because their goal is to maximize cumulative returns. In reinforcement learning, state transition probabilities are often unknown and must be estimated. However, in portfolio backtesting experiments, these probabilities are deterministic, making the conventional reinforcement learning approach to estimating state transitions suboptimal for portfolio optimization. Addressing this issue, this study decomposes the portfolio optimization into two core tasks: prediction and profit policy optimization and proposes a novel reinforcement learning framework that assumes deterministic state transition probabilities, comprised of three main modules: feature extraction, prediction, and profit strategy optimization. To model assets more effectively and comprehensively, we capture their temporal features, relational features, and market state. We introduce a patch-wise correlation method and attribute based gate to enhance feature extraction. In the profit policy module, we utilize a deterministic strategy, employing a recursive reinforcement learning method based on Monte Carlo sampling to train the policy network. This enables dynamic adjustments of asset investment weights, ensuring the maximization of cumulative returns. Extensive experiments conducted on cryptocurrency datasets demonstrate the superior performance of our approach, and achieving 36.6%-75.6% improvements in main measurements on cryptocurrency datasets.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】Reinforcement learning; Deterministic state transition probability; Portfolio optimization; Asset modeling
【发表时间】2025
【收录时间】2024-10-26
【文献类型】 实证数据
【影响因子】7.466
【主题类别】
区块链技术-协同技术-联邦学习
【Abstract】Federated Learning emerged as a promising solution to enable collaborative training between organizations while avoiding centralization. However, it remains vulnerable to privacy breaches and attacks that compromise model robustness, such as data and model poisoning. This work presents PRoT-FL, a privacy-preserving and robust Training Manager capable of coordinating different training sessions at the same time. PRoT-FL conducts each training session through a Federated Learning scheme that is resistant to privacy attacks while ensuring robustness. To do so, the model exchange is conducted by a "Private Training Protocol"through secure channels and the protocol is combined with a public blockchain network to provide auditability, integrity and transparency. The original contribution of this work includes: (i) the proposal of a "Private Training Protocol"that breaks the link between a model and its generator, (ii) the integration of this protocol into a complete system, PRoT-FL, which acts as an orchestrator and manages multiple trainings and (iii) a privacy, robustness and performance evaluation. The theoretical analysis shows that PRoT-FL is suitable for a wide range of scenarios, being capable of dealing with multiple privacy attacks while maintaining a flexible selection of methods against attacks that compromise robustness. The experimental results are conducted using three benchmark datasets and compared with traditional Federated Learning using different robust aggregation rules. The results show that those rules still apply to PRoT-FL and that the accuracy of the final model is not degraded while maintaining data privacy.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】Federated learning; Privacy; Robustness; Security; Blockchain; Cryptography
【发表时间】2025
【收录时间】2024-10-26
【文献类型】 实证数据
【影响因子】7.275
【主题类别】
区块链应用-虚拟经济-数字孪生
区块链技术-协同技术-物联网
【Abstract】
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】
【发表时间】2024
【收录时间】2024-10-26
【文献类型】 实验仿真
【Author】 Shahzad, Khuram Zafar, Abaid Ullah Shahzad, Muhammad Faisal Husnain, Mudassir Hayat, Khizar
【影响因子】7.096
【主题类别】
区块链应用-实体经济-电商领域
区块链治理-市场治理-行为分析
【Abstract】Product quality is essential for companies' success because it is integral to meeting customers' expectations. In this context, blockchain technology (BT) offers potential solutions for tracking products' origins and flows, eliminating or reducing fraudulent activities efficiently and effectively. Drawing upon signaling theory, this study investigates how BT's traceability and transparency attributes can enhance consumers' urge to buy impulsively and impulsive buying behavior. The results reveal that transparency positively affects perceived product quality and trust in BT-enabled e-commerce platforms. Moreover, traceability positively affects perceived product quality and product affection. The study also identifies that perceived product quality positively affects the urge to buy impulsively and product affection. In addition, product affection and consumers' trust positively affect the urge to buy impulsively and impulsive buying behavior. Furthermore, the urge to buy impulsively positively affects impulsive buying behavior. Finally, consumers' situations moderate the relationship between the urge to buy impulsively and impulsive buying behavior. The findings provide insight for e-commerce platforms and sellers to refine marketing strategies by providing BT-related signals.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】blockchain technology; consumers' situations; impulsive buying behavior; perceived product quality; traceability; transparency
【发表时间】2024
【收录时间】2024-10-26
【文献类型】 实证数据
【DOI】 10.1111/ijcs.13092
【影响因子】6.879
【主题类别】
区块链应用-虚拟经济-元宇宙
区块链应用-实体经济-智慧城市
【Abstract】Recent digital advancements have led the construction industry to reassess its core principles. Critical issues such as construction site impacts, aesthetics, methodologies, and sustainability are under rigorous scrutiny. The challenges hindering the digital transformation of construction remain unclear. Addressing the technical questions of when, where, why, and how the industry is evolving is crucial, especially as digital operations become more prevalent compared to traditional methods. The "digital twin" concept has emerged as a key approach in shaping the industry's future. Integrating Building Information Modelling (BIM) with the Internet of Things (IoT) has enhanced project engagement, though challenges persist. Traditionally, a digital twin represents the construction process and its interactions. But it misses the transactional and experiential aspects that integrate users into the process. Technologies like blockchain and the metaverse, combined with the digital twin, offer insights into the future of construction projects. Municipalities that adopt digital twins and metaverse representations of their commercial activities throughout construction phases are likely to set future standards for societal specifications. As some specifications such as architectural designs should be grounded in the diverse aspirations and experiences sought by citizens. This paper aims to explore the ways digital twins, smart urban environments, blockchain technology, and other reality capture datasets contribute to the vision of digital and physical construction domains. It examines the interaction and convergence of new spatial constructs, highlight the critical role of data acquisition technologies, and present a comprehensive framework for user experience and the future of Meta Smart Twin Cities.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】Meta smart twin city; Biotechnology; Metaverse; Architectural innovation; Socio-technical concerns
【发表时间】2024
【收录时间】2024-10-26
【文献类型】 观点阐述
【影响因子】6.757
【主题类别】
区块链应用-实体经济-食品供应链
区块链技术-平台项目-Hyperledger Fabric
【Abstract】Blockchain technology shows significant promise for addressing challenges within the agri-food supply chain. However, the effective application of blockchain platforms in this context is still an area of research. This study proposes a blockchain-based system that uses Hyperledger Fabric to manage agri-food supply chains based builder design patterns. The main focus is on preserving relationships, authorizations, and accurate traceability of food products throughout the supply chain. The system takes into account the various stakeholders involved in the food supply chain to ensure coordination and efficiency. It integrates multiple security mechanisms to enhance security and enforce adherence to chaincode, preventing unauthorised access to critical data or operations. Additionally, ownership and validity checks are incorporated for agreement issuance and asset generation, providing credentials for the legitimacy of linked agreements and organisational authorisation. The proposed system improves the security and integrity of the supply chain by using one-time agreements, which mitigates the risk of replay attacks or malicious activity. A web platform has been proposed to give users realtime visibility of a package's movement through the supply chain. This enables access to a detailed chronology of the product's movement and delivery steps by scanning the package's QR code. The proposed system is evaluated for performance using the Caliper tool to measure network throughput and transaction latency, which demonstrates the feasibility and efficiency of Hyperledger Fabric in optimising agri-food supply chains.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】Agrifood supply chain; Blockchain technology; Security mechanisms; Hyperledger Fabric; Caliper tool
【发表时间】2024
【收录时间】2024-10-26
【文献类型】 实验仿真
【Author】 Lazaroiu, George Gedeon, Tom Rogalska, Elzbieta Valaskova, Katarina Nagy, Marek Musa, Hussam Zvarikova, Katarina Poliak, Milos Horak, Jakub Cretoiu, Raluca Ionela Krulicky, Tomas Ionescu, Luminia Popa, Catalin Hurloiu, Lacramioara Rodica Nistor, Filip Avram, Laurentia Georgeta Braga, Viorica
【影响因子】6.574
【主题类别】
区块链应用-虚拟经济-元宇宙
区块链技术-协同技术-人工智能
【Abstract】Research background: Generative artificial intelligence (AI) and machine learning algorithms support industrial Internet of Things (IoT)-based big data and enterprise asset management in multiphysics simulation environments by industrial big data processing, modeling, and monitoring, enabling business organizational and managerial practices. Machine learning-based decision support and edge generative AI sensing systems can reduce persistent labor shortages and job vacancies and power productivity growth and labor market dynamics, shaping career pathways and facilitating occupational transitions by skill gap identification and laborintensive manufacturing job automation by path planning and spatial cognition algorithms, furthering theoretical implications for management sciences. Generative AI fintech, machine learning algorithms, and behavioral analytics can assist multi-layered payment and transaction processing screening with regard to authorized push payment, account takeover, and synthetic identity frauds, flagging suspicious activities and combating economic crimes by rigorous verification processes. Purpose of the article: We show that edge device management functionalities of cloud industrial IoT and virtual robotic simulation technologies configure plant production and route planning processes across cyber-physical production and industrial automation systems in multi-cloud immersive 3D environments, leading to tangible business outcomes by reinforcement learning and convolutional neural networks. Labor-augmenting automation and generative AI technologies can impact employment participation, increase wage and wealth inequality, and lead to potential job displacement and massive labor market disruptions. The deep learning capabilities of generative AI fintech in terms of adaptive behavioral analytics and credit scoring mechanisms can enhance financial transaction behaviors and algorithmic trading returns, identify fraudulent payment transactions swiftly, and improve financial forecasts, leading to customized investment recommendations and well-informed financial decisions. Methods: Machine learning-based study selection process and text mining systematic review management software and tools leveraged include Abstrackr, CADIMA, Colandr, DistillerSR, EPPI-Reviewer, JBI SUMARI, METAGEAR package for R, SluRp, and SWIFT-Active Screener. Such reference management systems are harnessed for methodologically rigorous evidence synthesis, study selection and characteristic extraction, predictive document classification, machine learning-based citation and record screening, bias assessment, article retrieval automation, and document classification and prioritization.Findings & value added: Industrial IoT and 3D augmented reality technologies can create business value by streamlining virtual product and remote asset management across extended reality-based navigation and robotic autonomous systems in smart factory environments by generative AI and machine learning algorithms, articulating business organizational level and theory of management implications. 3D simulation and operational modeling tools can execute and complete complex cognitive task-oriented and knowledge economy jobs, producing first-rate quality outputs swiftly while leading to unemployment spells, labor market disruptions, job displacement losses, and reduced earnings by machine learning clustering and spatial cognition algorithms. Generative AI decentralized finance, interoperable blockchain networks, cash flow management tools, and asset tokenization can mitigate fraud risks, enable digital fund and crypto investing servicing, and automate treasury operations by integrating real-time payment capabilities, routing and configurable workflows, and lending and payment technologies.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】generative artificial intelligence economics; fintech; labor market; metaverse enterprise; production management; cyber-physical manufacturing
【发表时间】2024
【收录时间】2024-10-26
【文献类型】 综述
【DOI】 10.24136/oc.3183
【影响因子】4.152
【主题类别】
区块链治理-技术治理-链上数据分析平台
【Abstract】Relationship analysis of cryptocurrencies is crucial for understanding and regulating their ecosystems with graph structures. In particular, the relationships of the UTXO-based cryptocurrencies, which were developed earlier, form ecosystems with more integrated and larger graph structures. It is a challenge to efficiently store such large graphs and to efficiently query and analyze these graphs. In this paper, we propose UTXOAnalysis to solve these problems. UTXOAnalysis is a distributed graph storage and analysis system with a three-level structure. In the data collection framework, UTXOAnalysis adopts batch queries and block pruning. In the parsing and storage framework, UTXOAnalysis utilizes the parallel approaches of multi- graph parsing and storage. UTXOAnalysis also provides these methods for incremental data. In the analysis framework, UTXOAnalysis supplies address relationship analysis, transaction relationship analysis, and cryptocurrency flow tracing, which are the three basic analysis methods. In our experiments, we collected data from Bitcoin and Zcash to demonstrate the efficiency of data collection, parsing, storage, and basic analysis. UTXOAnalysis is more efficient in storing and analyzing UTXO-based cryptocurrencies than the baseline methods.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】Blockchain; Cryptocurrency; Heterogeneous graph; Graph storage; Graph analysis
【发表时间】2024
【收录时间】2024-10-26
【文献类型】 实证数据
【Author】 Howson, Peter Rosales, Antulio Jutel, Olivier Gloerich, Inte Llorens, Mariel Garcia de Vries, Alex Crandall, Jillian Dolan, Paul
【影响因子】3.620
【主题类别】
区块链应用-虚拟经济-Web3
【Abstract】This paper explores how so-called 'Web3' blockchain projects are materially and socially constituted. A blockchain is an append-only distributed database. The technology is being hyped as applicable for a whole range of industries, social service provisions, and as a fix for economic disparities in communities left behind by mainstream financial systems. Drawing on case studies from our ongoing research we explain how, despite being virtual, Web3 projects are dependent on clearly defined spaces of production from which they derive their speculative value. We conceptualise this relationship as Crypto/Space, where space and blockchain software are mutually constituted. We consider how Crypto/Spaces are produced in three ways: 1) how project developers are adopting a parasitic relationship with host locations to appropriate energy, infrastructure, and local resources; 2) how projects enable 'virtual land grabs' where developers are engaging in land acquisitions, and associated displacement of local people, with no real intention to use the land for the declared purpose; and 3) how blockchain technology and speculative finance imaginaries are inspiring new anarcho-capitalist crypto-utopian 'Exit zones', often in the Global South. Far from being a zero-sum virtual game world, we argue that cryptocurrency projects are parasitic, often requiring predation on poor and otherwise marginalised communities to appropriate resources, onboard new users and enable favourable regulation.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】
【发表时间】2024
【收录时间】2024-10-26
【文献类型】 观点阐述
【Author】 Hu, Zhihua Kim, Bongjun Jeong, Junho
【影响因子】3.476
【主题类别】
区块链应用-实体经济-农业领域
区块链技术-平台项目-Hyperledger Fabric
【Abstract】Agriculture is essential for human survival facing critical issues such as limited access to modern machinery, a lack of comprehensive data, and difficulties in implementing insurance programs. To address these challenges, this study explores the potential of blockchain technology, finding that the Hyperledger Fabric can satisfy certain criteria vital for rectifying the existing issues due to its secure and scalable features. Utilizing the channel mechanism of Hyperledger Fabric, we developed a multi-channel network infrastructure to cater to the varying needs in agriculture. Each agricultural service is facilitated through its unique channel, accompanied by an easy-to-navigate webpage, enhancing user experience while ensuring data security. In our experiments, we deployed the system using Docker containers and virtual machines. Performance tests were conducted to evaluate the system's effectiveness in data sharing, machinery service coordination, and insurance claim processing. The results demonstrated that the system effectively improves data sharing efficiency, streamlines machinery service coordination, and enhances the transparency and reliability of insurance claims processing. These findings highlight the potential of our system to significantly enhance agricultural production efficiency. The flexible and expandable nature of this system offers tremendous potential for future improvements, aiming to fulfill the multifaceted demands of agriculture more effectively, thereby laying a robust foundation for significantly enhancing agricultural production efficiency.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】Distributed ledger; Fabrics; Insurance; Security; Peer-to-peer computing; Machinery; Blockchains; Scalability; Agricultural machinery; Data security; User experience; Information sharing; Smart agriculture; Agriculture; blockchain; Hyperledger fabric; multi-channel; scalability
【发表时间】2024
【收录时间】2024-10-26
【文献类型】 实验仿真
【Author】 Alamri, Bandar Richardson, Ita Crowley, Katie
【影响因子】3.476
【主题类别】
区块链应用-实体经济-身份管理
【Abstract】This paper presents an evaluation of a cybersecurity risk management and evaluation framework for Blockchain-based Identity Management Systems (BC-IdM) in the Health Internet of Things (HIoT). In this paper, thirteen experts were interviewed using a Delphi method to evaluate the framework, which includes the factors that are used to evaluate any HIoT BC-IdM system and the cybersecurity risk management processes and activities that should be applied. In addition, the Simple Multi-Attribute Rating Technique (SMART) was used in the interviews and questionnaires with the experts to assign weights to the twenty-six identified evaluation factors to rank them based on their importance. The identified factors are divided into four main categories: security and privacy, technical, HIoT-related considerations, and external aspects. This paper shows that the security and privacy factors are the most important among other factors. Using Delphi, an agreement on the details of the framework was sought, including the cybersecurity risk management processes and activities in the main phases: framing, assessment, responding, and mentoring of risks. This article identifies the main and subcategories of the evaluation factors and explains the framework content in detail. It presents recommendations and findings concerning Blockchain-based Identity Management Systems in Health Internet of Things. The framework plays a role in standardizing BC-IdM in HIoT and contributes to the applicability and reliability of such systems by considering security, privacy, technical, HIoT-related, and external considerations.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】Security; Consensus protocol; Risk management; Medical services; Computer security; Bitcoin; Peer-to-peer computing; Blockchains; Internet of Medical Things; Blockchain; cybersecurity risk management; Delphi; evaluation; health IoT; identity management; multi-criteria decision making
【发表时间】2024
【收录时间】2024-10-26
【文献类型】 实证数据
【Author】 Li, Dengjia Ma, Chaoqun Li, Hao Yang, Jinglan
【影响因子】3.399
【主题类别】
区块链应用-实体经济-融资租赁
【Abstract】Despite the recognized significance of blockchain in supply chain management literature, there has been a scarcity of studies empirically exploring the link between blockchain adoption and financing constraints. This paper delves into how blockchain adoption influences financing constraints, considering the moderating effects of environmental and firm-specific factors. Utilizing panel data from A-share listed firms in China over the period 2016-2021, our analysis reveals that blockchain adoption notably eases financing constraints. Additionally, we observe a spillover effect: the adoption of blockchain technology by a central enterprise can alleviate financing constraints for affiliated companies within their supply chain, including upstream and downstream firms. Our heterogeneity analysis indicates that the effectiveness of blockchain in reducing financing constraints is more pronounced in environments with robust internal and external governance and higher levels of marketization. Moreover, blockchain adoption can mitigate traditional finance's ownership bias against non-state-owned enterprises and the bargaining power disparities faced by central firms in the supply chain. In addition, in non-high-tech, non-heavy pollution, and non-manufacturing industries, firms can better alleviate financing constraints after adopting blockchain. These findings offer valuable insights for businesses looking to navigate the challenges and opportunities of mitigating financing constraints through blockchain adoption.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】Blockchain adoption; Financing constraints; Governance environment; Marketization; Non-SOEs; Bargaining power; Industry category
【发表时间】2024
【收录时间】2024-10-26
【文献类型】 实证数据
【Author】 Li, Houjian Luo, Fangyuan Guo, Lili
【影响因子】3.399
【主题类别】
区块链治理-市场治理-市场分析
【Abstract】Understanding Bitcoin's (BTC) performance and hedging effects under various uncertainties is crucial. This study combines time-varying Granger causality (TVGC) tests and wavelet timevarying parameter vector autoregression (TVP-VAR) methods to examine the relationship between Bitcoin (BTC) and climate uncertainty (SOI), geopolitical risk (GPR), economic policy uncertainty (EPU), crude oil volatility (OVX), and market volatility (VIX) across both time and frequency domains, from December 19, 2017, to October 16, 2023. The results show that in recent years, the long-term impact of SOI on BTC, as well as political and economic uncertainties, is hard to ignore, but BTC cannot serve as a safe-haven asset against SOI. Wavelet decomposition indicates that during extreme events, BTC exhibits a leading positive co-movement with EPU, GPR, VIX, and OVX in the long term, showing potential as a hedging asset. However, TVGC and wavelet decomposition spillover results further suggest that BTC's hedging capacity against different economic and political uncertainties may be limited during certain extreme events.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】Climate change; BTC; The wavelet TVP-VAR; Time-varying granger causality test
【发表时间】2024
【收录时间】2024-10-26
【文献类型】 实证数据
【作者】 张小苗; 惠怀海; 李铮; 王迪; 何嘉洪; 罗艺
【作者单位】中国西南电子技术研究所;
【文献来源】电讯技术
【复合影响因子】0.979
【综合影响因子】0.733
【主题类别】
区块链应用-实体经济-卫星互联网
【摘要】在卫星节点上构建区块链系统可有效消除星载数据协同的地域限制，同时减少数据泄露的风险，为卫星互联网提供信任机制的保障。针对区块链和卫星互联网深度融合时存在的网络拓扑高动态、计算资源和链路资源受限、存在蓄意攻击与破坏等问题，基于TrustZone构建了星载区块链边缘节点的多级安全架构，可有针对性地提高星载区块链边缘节点的物理节点、信息系统和可信数据的多级安全性，并在多级安全架构下从星载区块链边缘节点的计算、存储、传输和密码等方面开展了轻量化设计，进而通过星载区块链边缘节点多级安全模拟实验、轻量化设计效果对比分析和数据可信协同模拟实验验证了所提架构的有效性，可为下一步开展基于星载区块链边缘节点的卫星互联网数据应用研究提供技术参考。
【关键词】卫星互联网;;星载区块链;;边缘节点;;多级安全架构;;数据协同
【文献类型】 实验仿真
【发表时间】2024-10-26