【Author】 Zhu, Jizhong Zhou, Jialin Zhang, Di Gan, Wei Sun, Chao
【影响因子】11.446
【主题类别】
--
【Abstract】This paper focuses on the low-carbon trustworthy economic dispatch strategy of integrated energy industrial parks that merge integrated energy systems with high-carbon production enterprises. A ladder-type carbon trading mechanism is proposed with a particular emphasis on environmental protection and carbon reduction, which incorporates the carbon trading cost into the total dispatching cost and could incentivize the industrial park to operate in a low-carbon manner. A trustworthy data attestation and traceability framework based on blockchain technology is developed to ensure the trustworthiness of device and enterprise production, operation, and transaction data within the park, and to provide data query and traceability functions. Furthermore, the onchain and off-chain storage mechanisms and the internal and external dual-chain collaboration mechanisms are conducted to alleviate data management and storage pressures, isolate sensitive data, and satisfy differentiated data management needs. The simulation result demonstrates that applying the ladder-type carbon trading mechanism can effectively reduce the carbon emissions of industrial parks, and the proposed framework can be beneficial to accurate load forecasting and practical dispatch strategies.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】Integrated energy system; Blockchain; Industrial load; Carbon trading; Day-ahead economic dispatch
【发表时间】2025
【收录时间】2025-02-19
【文献类型】
【影响因子】11.446
【主题类别】
--
【Abstract】Machine learning models offer the capability to forecast future energy production or consumption and infer essential unknown variables from existing data. However, legal and policy constraints within specific energy sectors render the data sensitive, presenting technical hurdles in utilizing data from diverse sources. Therefore, we propose adopting a Swarm Learning scheme, which replaces the centralized server with a blockchain-based distributed network to address the security and privacy issues inherent in Federated Learning's centralized architecture. Within this distributed collaborative learning framework, each participating organization governs nodes for inter-organizational communication. Devices from various organizations utilize smart contracts for parameter uploading and retrieval. The consensus mechanism ensures distributed consistency throughout the learning process, guarantees the transparent trustworthiness and immutability of parameters on-chain. The efficacy of the proposed framework is substantiated across two real-world temporal and spatial series data modeling scenarios in energy systems: photovoltaic power generation forecasting and geophysical well log generation. Our approach shows superior performance compared to Local Learning methods while emphasizing enhanced data security and privacy over both Centralized Learning and Federated Learning methods.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】Swarm Learning; Series data; Blockchain; Distributed machine learning; Privacy-preserving computation
【发表时间】2025
【收录时间】2025-02-19
【文献类型】
【Author】 Muck, Matthias Schmidl, Thomas Wolf, Julian
【影响因子】9.848
【主题类别】
--
【Abstract】This study investigates the efficiency of cryptocurrency markets by examining the presence and exploitability of arbitrage opportunities. Using high-frequency data from the Binance Exchange, we implement a triangular arbitrage strategy, considering Bitcoin, Litecoin, and the U.S. Dollar. We find 4,879 possible arbitrage opportunities. Although these findings suggest potential inefficiencies, transaction costs and limited trading volumes in the order book eliminate their profitability. Consequently, centralized cryptocurrency markets exhibit a high degree of efficiency. Moreover, our results suggest that the mere number of triangular arbitrage opportunities is not a reliable indicator of market inefficiency.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】Triangular arbitrage; Cryptocurrencies; Market efficiency
【发表时间】2025
【收录时间】2025-02-19
【文献类型】
【影响因子】9.018
【主题类别】
--
【Abstract】The aviation industry's carbon emissions are forecast to rise to 22% by 2050, posing a significant challenge to the goal of achieving Net Zero Emissions by the same year. Regardless of the structural or agentic strategies implemented to reduce these emissions, ensuring effective traceability of emissions in airline operations is crucial, as it enables the development of effective mitigation measures. Existing systems fall short of effectively providing end-to-end traceability of emissions within an effective carbon accounting framework. Indirect emissions and the complexities associated with emissions tracking throughout the extended aviation sector also exacerbate carbon accounting and offsetting difficulties. In this paper, we present a blockchain-based framework to address these plausible challenges. The proposed work categorises both direct and indirect emissions under Scope 1, 2, and 3 classifications. A blockchain-based collaborative platform, also provides data transparency across all stakeholders, ensuring traceability and security in a decentralised and reliable manner. A prototype model of a blockchain-based system is therefore developed using Ethereum smart contracts. The paper presents a cost and security analysis of the system, while highlighting the challenges and opportunities for the development of sustainable aviation operations. The smart contract is made publicly available on Github for verification.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】Blockchain; carbon footprint traceability; carbon accounting; aviation industry; smart contract; net-zero
【发表时间】2024
【收录时间】2025-02-19
【文献类型】
【影响因子】8.562
【主题类别】
--
【Abstract】The excessive utilization of industrial output has drawn significant attention from authorities toward sustainable development. Given the substantial environmental challenges posed by the industrial sector, sustainable development has emerged as a paramount concern for scholars and organizations alike. In this context, considerable emphasis has been placed on the significance of digitization. Digital technologies, particularly blockchain technology (BCH) and digital finance (DF), are transforming the landscape of business and the economy, facilitating corporate sustainable development (CSD), enhancing corporate social practices, and fostering green innovation. Through the application of various econometric strategies using the Chinese business sector as a sample of the study, we found that BCH effectively promotes green innovation and corporate social activities. Additionally, our analysis underscores the critical role of DF in advancing corporate social practices and green innovation. Notably, we highlight the importance of human capital as a moderating factor that strengthens the relationships between BCH and CSD, as well as between digital finance and CSD. This study offers novel insights into ways, digital technology can enhance corporate sustainability practices and presents a framework that may be of significant utility to policymakers and decision-makers.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】block-chain technology; corporate sustainable development; digital finance; human capital; social change
【发表时间】2025
【收录时间】2025-02-19
【文献类型】
【DOI】 10.1002/sd.3319
【影响因子】7.307
【主题类别】
--
【Abstract】Facing the computational challenges in mobile devices within blockchain networks, particularly the scarcity and underutilization of computational resources, this paper introduces the CAGE Framework: a novel architecture based on cooperative game theory within alliance blockchains. Designed to optimize computational resource allocation across multiple mobile terminals, CAGE Framework leverages a tri-layer structure - comprising the Blockchain Network Layer, User Network Layer, and Distributed Collaborative Computing Layer - to facilitate efficient resource sharing and task scheduling. Through intelligent contracts, the framework automatically aggregates user demands, utilizing the InterPlanetary File System (IPFS) for data storage, thereby enhancing privacy protection and blockchain data throughput. Validated on the Hyperledger Fabric platform and benchmarked against state-of-the-art approaches, CAGE demonstrates superior transaction throughput, reduced latency, and enhanced resource efficiency. The core strategy, dubbed CAGE, is predicated on cooperative gaming, aiming to maximize user satisfaction by balancing energy consumption, computational load, and resource allocation multi-objectively. Experiments reveal a notable improvement in system load balancing (by 51%) and a significant reduction in energy consumption (by 62%), affirming the framework's efficacy in addressing computational resource deficiencies both within and outside the alliance under low energy and balanced load conditions. The CAGE Framework not only charts anew path for computational resource optimization in mobile blockchain networks but also lays a theoretical and practical foundation for the furtherance of blockchain technology application and optimization.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】Consortium blockchain; Multiple mobile terminals; Cooperative gaming; Collaborative computing
【发表时间】2025
【收录时间】2025-02-19
【文献类型】
CCF-A
【影响因子】7.231
【主题类别】
--
【Abstract】A Bitcoin miner who owns a sufficient amount of mining power can perform selfish mining to increase its relative revenue. Studies have demonstrated that the time-averaged profit of a selfish miner starts to rise once the mining difficulty level gets adjusted in favor of the attacker. Selfish mining profitability lies in the fact that orphan blocks are not incorporated into the current version of Bitcoin's difficulty adjustment mechanism (DAM). Therefore, it is believed that considering the count of orphan blocks in the DAM can result in complete unprofitability for selfish mining. In this paper, we disprove this belief by providing a formal analysis of the selfish mining time-averaged profit. We present a precise definition of the orphan blocks that can be incorporated into calculating the next epoch's target and then introduce two modified versions of DAM in which both main-chain blocks and orphan blocks are incorporated. We propose two versions of smart intermittent selfish mining, where the first one dominates the normal intermittent selfish mining, and the second one results in selfish mining profitability under the modified DAMs. Moreover, we present the orphan exclusion attack with the help of which the attacker can stop honest miners from reporting the orphan blocks. Using combinatorial tools, we analyze the profitability of selfish mining accompanied by the orphan exclusion attack under the modified DAMs. Our results show that even when considering orphan blocks in the DAM, selfish mining can still be profitable. However, the level of profitability under the modified DAMs is significantly lower than that observed under the current version of Bitcoin DAM, suggesting that orphan reporting can be an effective countermeasure against a payoff-maximizing selfish miner.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】Dams; Profitability; Bitcoin; Costs; Throughput; Switches; Standards; Q-learning; Proof of stake; Proof of Work; Selfish mining; bitcoin; blockchain
【发表时间】2025
【收录时间】2025-02-19
【文献类型】
【Author】 Hina, Maryam Islam, Najmul Luo, Xin (Robert)
CCF-C
【影响因子】6.969
【主题类别】
--
【Abstract】To facilitate the promotion of sustainable consumption decision-making, organizations might employ blockchain technology to offer transparent information regarding the sustainability of their products. Nonetheless, consumers often seek supplementary information from diverse sources. The inconsistent or conflicting information across these sources can complicate the process of making sustainable consumption decisions. Prior studies lack an understanding of how blockchain transparency and information-seeking shape individual decision-making regarding sustainable consumption. In this study, building on signaling theory, we have developed a model to understand how blockchain transparency and the consumers' information-seeking tendencies may reduce sustainable product uncertainty. To analyze our research model, first, we conducted five focus group interviews with 21 participants to understand their information needs while making sustainable consumption decisions in the context of the fashion apparel industry. The results of the focus groups helped us craft a scenario and user interface (UI) for a novel blockchain-based app for sustainable consumption. We then collected data from 282 European consumers and examined direct path coefficients and indirect moderated mediation effects. The findings highlight that blockchain transparency affects the trustworthiness of product sustainability and improves consumer satisfaction, which in turn reduces sustainable product uncertainty. The relationship between blockchain transparency and satisfaction is reduced by information-seeking. This finding implies that the consumers' experience of blockchain transparency in terms of enhanced satisfaction is not always consistent and instead depends on their inclination to seek information.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】Blockchain; Transparency; Sustainability; Information-seeking; Product uncertainty
【发表时间】2025
【收录时间】2025-02-19
【文献类型】
【Author】 Xing, Yunfei Zhang, Justin Z. He, Yuming Li, Yueqi
【影响因子】6.793
【主题类别】
--
【Abstract】As blockchain technology advances, non-fungible tokens (NFTs) are emerging as unconventional assets in the commercial market. However, it is necessary to establish a comprehensive NFT ecosystem that addresses the prevailing public concerns. This study aimed to bridge this gap by analyzing user-generated content on prominent social media platforms such as Twitter, Weibo, and Reddit. Employing text clustering and topic modeling techniques, such as Latent Dirichlet Allocation, we constructed an analytical framework to delve into the intricacies of the NFT ecosystem. Our investigation revealed seven distinct topics from Twitter and Reddit data and eight topics from Weibo data. Weibo users predominantly engaged in reviews and critiques, whereas Twitter and Reddit users emphasized personal experiences and perceptions. The NFT ecosystem encompasses several crucial elements, including transactions, customers, infrastructure, products, environments, and perceptions. By identifying the prevailing trends and common issues, this study offers valuable guidance for the development of NFT ecosystems.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】NFTs; Public opinion; Comparative analysis; Text clustering; Topic identification; Twitter; Weibo; Reddit
【发表时间】2025
【收录时间】2025-02-19
【文献类型】
【影响因子】6.793
【主题类别】
--
【Abstract】Many attempts have been made to identify barriers to blockchain adoption in supply chain; however, barriers to blockchain adoption in supply chain finance (SCF) are underexplored. This study prioritizes barriers to blockchain adoption in SCF and evaluates the barrier level of each alternative participant. We propose an integrated decision model to prioritize the barriers and evaluate their levels of alternative participants. To determine the barriers, we conducted a literature review. We then introduce an integrated weight calculation method by combining interval-valued Fermatean fuzzy (IVFF)-optimistic-pessimistic-utility values-based and IVFF-RS (ranking sum) methods to determine the barrier weights. To evaluate the barrier level of each alternative participant in SCF, the integrated IVFF-RAFSI (Ranking of Alternatives through Functional Mapping of Criterion Subintervals into a Single Interval) model is presented to rank the barrier, which uses a power-weighted aggregation operator to fuse experts' opinions. A case study demonstrates the practicality of the integrated IVFF-RAFSI model. The results show that uncertain and competitive markets (weighted at 0.0676) are the most significant barriers. This finding also suggests that small and medium-sized processing enterprises have the highest barriers to blockchain adoption. Sensitivity and comparative analyses validate the steadiness and competency of the proposed model. These results indicate that the proposed methodology provides a systematic technique for analyzing barriers to blockchain applications in SCF.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】Blockchain; RAFSI model; Supply chain finance; Interval-valued Fermatean fuzzy
【发表时间】2025
【收录时间】2025-02-19
【文献类型】
【Author】 Benedek, Botond Nagy, Balint Zsolt
【影响因子】6.793
【主题类别】
--
【Abstract】The asymmetries of factors influencing the return of cryptocurrencies have already been well documented; however, in the case of NFTs, only information asymmetries and hedging properties related to asymmetries were studied. Therefore, the present study examines factors affecting NFT returns, from market-related factors (crypto-market index return and stock market index return) to the Amihud illiquidity ratio and Google search trends during different market conditions. The wavelet coherences-based methodology was applied separately during the boom, bust, normal, and turbulent periods identified by structural breakpoints. Based on 14 NFT projects between April 2019 and July 2022, results show two fundamental asymmetries influencing these NFT returns. First, there is an asymmetry in the behavior of the factors in different periods; second, there is an asymmetry in how illiquidity manifests itself over NFTs that do or do not possess cash flow-generating potential.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】Non-fungible tokens; Partial wavelet coherence; Multiple wavelet coherence; Multiple endogenous structural breaks; G12; G14; C58
【发表时间】2025
【收录时间】2025-02-19
【文献类型】
【Author】 Liu, Yanchu Zhang, Yu Zheng, Duosi
【影响因子】6.793
【主题类别】
--
【Abstract】In 2021, 12 fraudulent cases were identified in the Chinese carbon market. As a critical component of this emerging market, China's carbon-credit scheme in the automotive sector faces several shortcomings, including informational opacity and operational inefficiency, which affect market functionality and fairness. This study develops an information system that integrates blockchain technology and the Internet of Things to manage a carbon-credit scheme. Specifically, we attached carbon credits to each vehicle with radio frequency identification electronic tags and a chained data structure to ensure the traceability and reliability of information flow. We use the distributed ledger technology and establish five distinct types of smart contracts for decentralized operations to ensure that all procedures of the Chinese carbon-credit scheme are standardized and under public scrutiny. The proposed infrastructure has the potential to significantly enhance the transparency and efficiency of China's carbon-credit schemes.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】Carbon credit; Blockchain; Internet of things; Information system
【发表时间】2025
【收录时间】2025-02-19
【文献类型】
【影响因子】6.793
【主题类别】
--
【Abstract】This review synthesizes 48 academic studies on Initial Coin Offerings (ICOs) from 2018 to 2023, employing bibliometric and content analyses to illuminate their complexities and innovation in entrepreneurial finance. It identifies four key themes: (1) regulatory intricacies, market transformation, and strategic implications for emerging ventures; (2) the opportunities and challenges presented, and key factors influencing the success of ICOs; (3) ICOs and entrepreneurial finance; and finally, (4) review of reviews. By examining the intersection of legal frameworks, disruptive potential, and stakeholder challenges, this interdisciplinary perspective captures the essence of ICOs and charts a course for future inquiry. It serves as a pivotal reference for researchers, practitioners, and regulators to understand the multifaceted ICO landscape and its implications for the future of finance.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】Entrepreneurial finance; Initial coin offerings; ICOs; Tokenomics; ICO regulations; Conceptual review; G23; G24; K22; O31
【发表时间】2025
【收录时间】2025-02-19
【文献类型】
【Author】 Hu, Xiaoyan Gui, Meiqun Cheng, Guang Li, Ruidong Wu, Hua
【影响因子】6.348
【主题类别】
--
【Abstract】Due to its anonymity and decentralization, Bitcoin has long been a haven for various illegal activities. Cybercriminals generally legalize illicit funds by Bitcoin mixing services. Therefore, it is critical to investigate the mixing services in cryptocurrency anti-money laundering. Existing studies treat different mixing services as a class of suspicious Bitcoin entities. Furthermore, they are limited by relying on expert experience or needing to deal with large-scale networks. So far, multi-class mixing service identification has not been explored yet. It is challenging since mixing services share a similar procedure, presenting no sharp distinctions. However, mixing service identification facilitates the healthy development of Bitcoin, supports financial forensics for cryptocurrency regulation and legislation, and provides technical means for fine-grained blockchain supervision. This paper aims to achieve multi-class Bitcoin Mixing Service Identification with a Graph Classification (BMSI-GC) model. First, BMSI-GC constructs 2-hop ego networks (2-egonets) of mixing services based on their historical transactions. Second, it applies graph2vec, a graph classification model mainly used to calculate the similarity between graphs, to automatically extract address features from the constructed 2-egonets. Finally, it trains a multilayer perceptron classifier to perform classification based on the extracted features. BMSI-GC is flexible without handling the full-size network and handcrafting address features. Moreover, the differences in transaction patterns of mixing services reflected in the 2-egonets provide adequate information for identification. Our experimental study demonstrates that BMSI-GC performs excellently in multi-class Bitcoin mixing service identification, achieving an average identification F1-score of 95.08%.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】Bitcoin; Anti-money laundering; Mixing service; Ego network; Graph classification
【发表时间】2024
【收录时间】2025-02-19
【文献类型】
【Author】 Pan, Liwei Huo, Baofeng Hong, Xianpei
【影响因子】6.345
【主题类别】
--
【Abstract】Food safety is a worldwide concern, and ensuring traceability within the agricultural supply chain is crucial. To improve the quality of agricultural products, many agribusinesses are implementing blockchain technology for traceability, yet academic research in this area remains sparse. This study employs a mixed-methods approach to investigate how blockchain traceability technology fits with food safety assessment and influences the attractiveness of agri-food. Firstly, we identify the essential features of blockchain traceability technology and the technological concerns that assist consumers in recognizing food safety through interviews conducted with 30 participants. Secondly, drawing from the qualitative insights, we develop a theoretical model based on tasktechnology fit theory and analyze data from 450 survey respondents to assess how this fit, along with technology concerns, impacts the appeal of agricultural products. Our research offers significant practical insights for the implementation of blockchain traceability technology and the design of traceability interfaces.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】Blockchain traceability technology; Food safety; Task-technology fit; Data falsification; Agri-food appeal
【发表时间】2025
【收录时间】2025-02-19
【文献类型】
【Author】 Rashid, Mohammad Rifat Ahmmad Al Rafi, Abdullah Islam, Md. Ashraful Sharkar, Sifat Ullah Rafi, Ziaul Haque Hasan, Mahamudul Ali, Md Sawkat Khan, M. Saddam Hossain
【影响因子】6.189
【主题类别】
--
【Abstract】This paper introduces a blockchain-based framework designed to enhance the land management system in Bangladesh by addressing issues such as data fragmentation, corruption, and inefficiencies in land registration and titling. The proposed system integrates blockchain technology with smart contracts, IoT capabilities, and AI across five distinct layers: blockchain layer, stakeholder access layer, AI layer, IoT layer, and integration layer. These layers automate processes such as land sales, ownership verification, and real-time monitoring, reducing manual intervention and minimizing opportunities for fraudulent activities. The study combines a detailed review of existing challenges and technological solutions with an assessment of the system's performance based on metrics like transaction speed, resource consumption, and cost efficiency. Findings indicate that the framework enhances transparency, reduces corruption, and improves efficiency in land management, aligning with international best practices. Additionally, the discussion highlights the importance of integrating off-chain solutions to manage transaction costs and emphasizes the need for legal and regulatory adaptation for the successful implementation of blockchain technology. A phased implementation strategy begins with local community engagement and scales to broader oversight, aiming for a sustainable and effective approach to land governance.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】Block chain; Decentralized applications; Land management; Smart contact
【发表时间】2025
【收录时间】2025-02-19
【文献类型】
【Author】 Liu, Miaohui Xin, Xu Wang, Xiaoli Zhang, Tao Chen, Kang
【影响因子】6.173
【主题类别】
--
【Abstract】The container liner shipping industry plays a crucial role in intercontinental trade. In contrast to other modes of transportation, container shipping is subject to seasonal fluctuations in shipping demand. This phenomenon leads shipping companies to oversell slots in the contract market during the high-demand season. Fortunately, the rise of blockchain technology in the container shipping industry offers a potential solution in the form of a blockchain sales channel (BC). In addition, this BC can also enhance logistics transparency in comparison to the traditional sales channel (TC), which in turn increases the trust level of shippers. Under this background, we develop a two-stage Stackelberg game model to address the optimal sales channel selection problem, which involves a shipping company and multiple shippers. This model comprehensively considers the shipping demand seasonal fluctuations, the overselling behavior of the shipping company (under TC) and the higher trust level of shippers (under BC). We analyze the pricing strategies of the shipping company and the slot ordering strategies of shippers and investigate the optimal sales channel for stakeholders. Additionally, we discuss the impact of government subsidies on social welfare under the BC. The results show that i) the growth of logistics transparency may benefit shippers but sometimes damage the interests of the shipping company. The greater the degree of overselling compensation, the more unfavorable it is to shippers' interests. ii) The emergence of an optimal sales channel for stakeholders depends on the extent of shipping demand seasonal fluctuations, the relationship between the number of slots allocated to the contract and spot markets under BC and TC, and overselling compensation. iii) Government subsidies for blockchain technology can facilitate dual growth in social welfare and supply chain profits. These findings have implications for shipping companies and shippers in selecting sales channels and in providing policy recommendations to governments.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】Slot allocation; Demand seasonal fluctuation; Overselling behavior; Logistics transparency; Stackelberg game; Blockchain technology
【发表时间】2025
【收录时间】2025-02-19
【文献类型】
【影响因子】5.711
【主题类别】
--
【Abstract】The Internet of Medical Things (IoMT) is getting extreme attraction as it motivates unprecedented growth in the healthcare industry. Security breaches in IoMT can lead to threatening patients' lives. For IoMT, existing medical remote attestation techniques (EMRATs) have limitations such as neglecting operational symptoms of compromised systems, like inconsistent medical sensor readings. Moreover, EMRATs do not enable medical-forensic-based attestation history and are inefficient for mutual attestation between a doctor network and a sensor network monitoring a patient. This mutual attestation guarantees safe remote surgeries. In this paper for IoMT, we present a novel remote attestation protocol, BDMFA (Blockchainsupported and Deep learning Medical Forensic-enabling Attestation), to overcome the limitations of EMRATs. BDMFA utilizes deep learning and Blockchain to learn from sensor readings and store attestation history. We prove that BDMFA is resilient to a higher number of attacks than that resisted by EMRATs. Moreover, we present a proof-of-concept implementation for BDMFA using SMART (Secure and Minimal Architecture for Root of Trust). We proved the practical feasibility of BDMFA by implementing it using Omnetpp equipped with Castalia. For a system with 50 patient-sensors and 25 doctor-terminals, BDMFA needed only 2.6 s to complete attestation and less communication cost than that needed for related state-of-the-art protocols by 28.4%. For larger systems, we carried comparative analysis confirming that our proposed protocol BDMFA requires less cost and is more scalable and efficient than related protocols.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】Internet of Medical Things; Blockchain; Attestation; Deep learning; Operational semantics
【发表时间】2025
【收录时间】2025-02-19
【文献类型】
【Author】 Bouraga, Sarah
【影响因子】5.675
【主题类别】
--
【Abstract】Decentralized Applications (DApps) are increasingly popular. Many projects are proposed by blockchain enthusiasts, but many of these projects fail. In order to stimulate the development of successful DApps, clear guidelines and best practices are needed. Design patterns and architectural principles are already available in the literature. While extremely valuable for technical people, recommendations regarding the conceptual design of a DApp are missing: what are the elements to take into account to define a proper DApp project before starting the development per se? This work aims to address this question. The result will be a framework meant for business-oriented people, which can be used as a starting point in a DApp project. Hence, this work has implications for both practitioners and theoreticians. On the one hand, practitioners can use the framework as a set of guidelines to help them properly think out their projects. Investors and users can also use the framework as an assessment tool for a project. On the other hand, this work also contributes to the body of knowledge related to blockchain development.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】Blockchain; Decentralized application; Requirements engineering
【发表时间】2025
【收录时间】2025-02-19
【文献类型】
【Author】 Sharma, Adit Lashkari, Arash Habibi
CCF-B
【影响因子】5.493
【主题类别】
--
【Abstract】Encrypted traffic detection and classification is a critical domain in network security, increasingly essential in an era of pervasive encryption. This survey paper delves into integrating advanced Machine Learning (ML) and Deep Learning (DL) techniques to address the challenges of robust encryption methods and dynamic network behaviors. Despite notable advancements, there remains a substantial gap in the operational application of these technologies, often constrained by scalability, efficiency, and adaptability to varied encryption standards. We critically review existing methodologies from 7 surveys and 82 related technical papers, highlight the shortcomings, and propose future research directions. Our analysis underscores the need to develop innovative, resource-efficient models that seamlessly adapt to new threats and encryption techniques without compromising performance. Additionally, we advocate for creating comprehensive datasets that merge encrypted and non-encrypted traffic to enhance model training and testing. This survey maps out the trajectory of recent developments and charts a course for future research that could significantly enhance encrypted traffic management and security capabilities.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】Network traffic analysis; Encrypted traffic analysis; Encrypted traffic datasets; Network traffic analyzers; Encrypted traffic detection; Network traffic classification; Mobile traffic classification; ETC
【发表时间】2025
【收录时间】2025-02-19
【文献类型】
【影响因子】5.405
【主题类别】
--
【Abstract】This paper proposes a novel Privacy-preserving and Accountable Billing (PA-Bill) protocol for peer-to-peer energy trading markets. It addresses the challenges of discrepancies between committed and delivered energy volumes, ensuring accurate billing, privacy, and accountability. PA-Bill employs a universal cost-splitting mechanism to enhance fairness and prevent indirect privacy leakage. The protocol leverages homomorphic encryption to protect user data and uses blockchain technology to maintain accountability through an immutable and transparent distributed ledger. Additionally, it includes a dispute resolution mechanism to rectify erroneous bill calculations and identify responsible parties, thus ensuring non-repudiation. Our experimental and theoretical evaluations demonstrates that PA-Bill effectively supports large communities of up to 2000 households, offering a computationally efficient, privacy-preserving, and accountable billing solution in a semi-decentralised manner.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】Billing; Privacy; Accountability; Peer-to-peer energy market; Homomorphic encryption; Blockchain
【发表时间】2025
【收录时间】2025-02-19
【文献类型】
【影响因子】5.107
【主题类别】
--
【Abstract】We provide comprehensive background regarding the Ethereum blockchain protocol, focusing especially on the economic incentives of participants. We begin by clarifying the transaction lifecycle from the user perspective, explaining how user transactions are submitted and settled on the blockchain. Thereafter, we explain how the Ethereum protocol selects proposers to propose blocks of transactions for inclusion on the blockchain and also attesters to vote for or against those blocks. We discuss both how the Proof-of-Stake protocol is used to select proposers and attesters, and also how the Gasper protocol is used to aggregate attester votes which thereby determine the finalized blockchain. Finally, we discuss how builders, searchers and relays have arisen to support and enhance the Ethereum block production process. Through our discussion, we clarify the economic trade-offs faced by each participant and the associated real-world decision variables for each participant.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】Ethereum; Proof-of-Stake; Staking; Proposer-Builder Separation; Gasper; EIP-1559; Proposer; Attester; Builder; Relay; Maximal Extractable Value; MEV; Staking pools; Liquid staking; Liquid Staking Tokens; LSTs
【发表时间】2025
【收录时间】2025-02-19
【文献类型】
【Author】 Ahmad, Syed Zubair Qamar, Farhan
【影响因子】4.996
【主题类别】
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【Abstract】IoT device security has become a major concern as a result of the rapid expansion of the Internet of Things (IoT) and the growing adoption of cloud computing for central monitoring and management. In order to provide centrally managed services each IoT device have to connect to their respective High-Performance Computing (HPC) clouds. The ever increasing deployment of Internet of Things (IoT) devices linked to HPC clouds use various medium such as wired and wireless. The security challenges increases further when these devices communicate over satellite links. This Satellite-Based IoT-HPC Cloud architecture poses new security concerns which exacerbates this problem. An intrusion detection technology integrated in the central cloud is suggested as a potential remedy to monitor and detect aberrant activity within the network in order to allay these worries. However, the enormous amounts of data generated by IoT devices and their constrained computing power dose not allow to implement IDS techniques at source and renders towards typical central Intrusion Detection Systems (IDS) ineffectiveness. Moreover, to protect these systems, powerful intrusion detection techniques are required due to the inherent vulnerabilities of IoT devices and the possible hazards during data transmission.During the course of literature survey it is revealed that the research work has been done to detect few types of attacks by using the old school model of IDS. The computational expensiveness in terms of processing time is also an important parameter to be considered. This work introduces a novel Embedded Hybrid Deep Learning-based intrusion detection technique (EHID) based on embedded hybrid deep learning that is created specifically for IoT devices linked to HPC clouds via satellite connectivity. Two Deep Learning (DL) algorithms are integrated in the proposed method to improve detection abilities with decent accuracy while considering the processing time and number of trainable parameters to detect 14 types of threats. It segregates among the normal and attack traffic. We also modify the conventional IDS approach and propose architectural change to harness the processing power of central server of cloud. This hybrid approach effectively detects threats by harnessing the computing power available at HPC cloud along with leveraging the power of AI. Additionally, the proposed system enables real-time monitoring and detection of intrusions while providing monitoring and management services through HPC using IoT-generated data. Experiments on Edge-IIoTset Cyber Security Dataset of IoT & IIoT indicate improved detection accuracy, reduced false positives, and efficient computational performance.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】Deep learning (DL); Machine learning (ML); IoT; Satellite communication; High-performance computing (HPC) clouds; Embedded hybrid deep learning-based intrusion detection technique (EHID); Intrusion detection systems (IDS)
【发表时间】2024
【收录时间】2025-02-19
【文献类型】
【Author】 Morone, Giovanni Ciancarelli, Irene Calabro, Rocco Salvatore Cerasa, Antonio Iosa, Marco Gimigliano, Francesca
【影响因子】4.895
【主题类别】
--
【Abstract】Background and Objective: The metaverse refers to a digital realm accessible via internet connections using virtual reality and augmented reality glasses for promoting a new era of social rehabilitation. It represents the next-generation mobile computing platform expected to see widespread utilization in the future. In the context of rehabilitation, the metaverse is envisioned as a novel approach to enhance the treatment of human functioning exploiting the "synchronized brains" potential exacerbated by social interactions in virtual scenarios.Results: The metaverse emerges as an ideal domain for adapting the principles of the-International Classification of Functioning. Its intrinsic capacity to simulate interactions within virtual environments shared by multi-users, while providing a profound sense of presence and comprehensive perception, should facilitate learning and experiential understanding. Technical and conceptual aspects are currently under definition, including the interplay with artificial intelligence, definition of social metrics performance, and the utilization of blockchain technology for economic purposes.Conclusion: Building upon these foundations, this paper explores potential areas of metaverse applications in rehabilitation and examines how they may facilitate the pillars outlined in the World Health Organization's Rehabilitation 2030 call for action.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】metaverse; neurorehabilitation; augmented reality; ICF; disability
【发表时间】2025
【收录时间】2025-02-19
【文献类型】
【Author】 Gayathri, M. Gomathy, C.
【影响因子】4.790
【主题类别】
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【Abstract】The advancements in telematics and communication technology for automobiles have contributed to the development of Vehicular ad Hoc Networks (VANETs). These networks serve as the foundation for Intelligent Transportation Systems (ITS). Communication across various VANET entities is challenging due to the open communication environment and the highly dynamic nature of VANETs. One of the major challenges in VANETs is ensuring stable and secure transmission. To address these factors, several studies have been conducted. The article discusses a clustering algorithm for VANETs that leverages SCVAN-DPSO to create stable clusters and provide secure communication for mitigating malicious nodes. Additionally, Hyperelliptic Curve Cryptography (HECC) with signcryption in blockchain is proposed. This algorithm is designed to identify and mitigate malicious nodes, ensuring robust and secure communication within the network. To verify vehicles in VANETs, this study also suggests a safe and reliable key management method that generates and stores cryptographic keys using blockchain's distributed ledger technology. By doing so, the risk of rogue nodes is reduced, and a safe, stable connection between vehicles is guaranteed. This work has been implemented using NS 3.34 simulation with the SUMO real-time traffic mobility simulator, and its performance has been evaluated. The proposed algorithm SCVAN-BKM provides a 99.6 % packet delivery ratio for 20 nodes, 0.4 % packet loss, end-to-end delay of 32.65 ms, throughput of 9.522 Mbps, and a cluster lifetime of 105 s. As the number of nodes increases in the communication zone, stable communication is maintained due to the clustering algorithm used in the proposed approach, as cluster formation supports stability in the high-mobility nature of vehicles, while secure communication is ensured using blockchain technology. The findings demonstrate that our approach is more effective and yields better outcomes than existing systems.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】Blockchain; Swarm clustering; Trust based authentication; VANET
【发表时间】2024
【收录时间】2025-02-19
【文献类型】
【影响因子】4.747
【主题类别】
--
【Abstract】Ethereum, as one of the most active cryptocurrency trading platforms, has garnered significant academic interest due to its transparent and accessible transaction data. In recent years, phishing scams have emerged as a serious criminal activity on Ethereum. Although most studies model Ethereum account transactions as networks and analyze them using traditional machine learning or network representation learning techniques, these approaches often rely solely on the latest static transaction records or use manually designed features while neglecting transaction histories, thus failing to fully capture the dynamic interactions and potential trading patterns between accounts. This article introduces an innovative multiperspective cascaded dynamic graph neural network model named DMPCG, which extracts phishing transaction data from authoritative databases like blockchain explorers to construct transaction network graphs. The model elevates the analysis from the microscopic features of nodes to the macroscopic dynamics of the entire network, integrating the attributes of static snapshot graphs with the evolution of dynamic trading networks, significantly enhancing the accuracy of phishing detection. Experimental results demonstrate that the DMPCG method achieves an impressive precision of 92.6% and an F1-score of 90.9%, outperforming existing baseline models and traditional subgraph sampling techniques.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】Phishing; Blockchains; Feature extraction; Electronic mail; Data mining; Real-time systems; Data models; Spatiotemporal phenomena; Research and development; Monitoring; Blockchain; DMPCG; ethereum; phishing scams detection
【发表时间】2024
【收录时间】2025-02-19
【文献类型】
【Author】 Sornette, Didier Zhang, Yu
【影响因子】3.778
【主题类别】
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【Abstract】We study the temporal evolution of the holding-time distribution of bitcoins and find that the average distribution of holding-time is a heavy-tailed power law extending from one day to over at least 200 weeks with an exponent approximately equal to 0.9, indicating very long memory effects. We also report significant sample-to-sample variations of the distribution of holding times, which can be best characterized as multiscaling, with power-law exponents varying between 0.3 and 2.5 depending on bitcoin price regimes. We document significant differences between the distributions of book-to-market and of realized returns, showing that traders obtain far from optimal performance. We also report strong direct qualitative and quantitative evidence of the disposition effect in the Bitcoin Blockchain data. Defining age-dependent transaction flows as the fraction of bitcoins that are traded at a given time and that were born (last traded) at some specific earlier time, we document that the time-averaged transaction flow fraction has a power law dependence as a function of age, with an exponent close to -1.5, a value compatible with priority queuing theory. We document the existence of multifractality on the measure defined as the normalized number of bitcoins exchanged at a given time.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】Bitcoin holding time; Bubbles and drawdowns; Multiscaling; Book-to-market returns and realized return; Disposition effect; Multifractality
【发表时间】2025
【收录时间】2025-02-19
【文献类型】
【Author】 Jin, Yuhang Ling, Li
【影响因子】3.515
【主题类别】
--
【Abstract】Plagiarism in software code and hardware design threatens the open-source movement and the software and hardware industries. It is essential to differentiate between the unethical act of plagiarism and the legitimate use of open-source resources. Existing copyright protection measures, such as license design, inadequately address copyright ownership and protection issues. Furthermore, they fail to detect plagiarism methods for open-source hardware projects, such as circuit location modification. To address these challenges, this paper proposes a blockchain-based copyright management scheme, which introduces a general originality detection model based on community detection, extracting adjustable granularity digests from code and design files. These digests are stored on a peer-to-peer blockchain, enabling nodes to verify the originality via smart contracts. Additionally, the scheme improves the storage structure, protecting the rights of authors and contributors. Experimental results demonstrate the effectiveness and runtime efficiency of the proposed model in extracting digests for blockchain storage while maintaining verification accuracy. The scheme offers enhanced generality, practical performance, and suitability for distributed development and maintenance, with considerable implications for evidence gathering, fostering innovation and integrity.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】Codes; Blockchains; Licenses; Copyright protection; Open source software; Peer-to-peer computing; Protection; blockchain; copyright management; open-source software and hardware; originality detection
【发表时间】2025
【收录时间】2025-02-19
【文献类型】
【Author】 Bathula, Peda Narayana Sreenivasulu, M.
【影响因子】3.515
【主题类别】
--
【Abstract】The importance of secure data sharing in fog computing is increasing due to the growing number of Internet of Things (IoT) devices. This article addresses the privacy and security issues brought up by data sharing in the context of IoT fog computing. The suggested framework, called "BlocFogSec", secures key management and data sharing through blockchain consensus and smart contracts. Unlike existing solutions, BlocFogSec utilizes two types of smart contracts for secure key exchange and data sharing, while employing a consensus protocol to validate transactions and maintain blockchain integrity. To process and store data effectively at the network edge, the framework makes use of fog computing, notably reducing latency and raising throughput. BlocFogSec successfully blocks unauthorized access and data breaches by restricting transactions to authorized nodes. In addition, the framework uses a consensus protocol to validate and add transactions to the blockchain, guaranteeing data accuracy and immutability. To compare BlocFogSec's performance to that of other models, a number of simulations are conducted. The simulation results indicate that BlocFogSec consistently outperforms existing models, such as Security Services for Fog Computing (SSFC) and Blockchain-based Key Management Scheme (BKMS), in terms of throughput (up to 5135 bytes per second), latency (as low as 7 ms), and resource utilization (70% to 92%). The evaluation also takes into account attack defending accuracy (up to 100%), precision (up to 100%), and recall (up to 99.6%), demonstrating BlocFogSec's effectiveness in identifying and preventing potential attacks.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】Technological innovation; Data privacy; Accuracy; Computational modeling; Smart contracts; Throughput; Consensus protocol; Internet of Things; Resource management; Edge computing; BlocFogSec; Internet of Things (IoT); fog computing; blockchain
【发表时间】2025
【收录时间】2025-02-19
【文献类型】
【影响因子】3.515
【主题类别】
--
【Abstract】This study examines secure and effective data sharing methods for edge computing networks. Traditional methods of sharing data at the edge have issues with security, speed, and consensus. The goal is to develop a Blockchain-based Secure Data Sharing Framework (BSDSF) capable of improving data integrity, latency, and overall network efficiency for edge-cloud computing applications. BSDSF proposes using blockchain technology with Byzantine Fault Tolerance (BFT) and smart contract-based validation as a new method of secure data sharing. It has a two-tiered consensus protocol to meet the needs of edge computing, which requires instantaneous responses. BSDSF employs Byzantine fault tolerance to deal with errors and protect against attacks. Smart contracts automate validation and consensus operations, while edge computing processes data at the attack site. Node validation and failure detection methods monitor network quality and dependability, while system security ensures secure communication between nodes. BSDSF is an important step toward digital freedom and trust by protecting security and improving transaction reliability. The framework demonstrates a reduction in transaction latency by up to 30% and an increase in throughput by 25% compared to traditional edge computing models, positioning BSDSF as a pivotal solution for fostering digital freedom and trust in edge computing environments.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】Fault tolerance; Data integrity; Fault tolerant systems; Smart contracts; Throughput; Real-time systems; Consensus protocol; Security; Standards; Edge computing; Byzantine Fault Tolerance (BFT); blockchain-driven; edge computing networks; consensus contract; data validation contract; node validation contract
【发表时间】2025
【收录时间】2025-02-19
【文献类型】
【Author】 Wen, Yean-Fu Chen, Ming-Fang
【影响因子】3.476
【主题类别】
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【Abstract】In the proof-of-work (PoW) blockchain consensus mechanism, miners perform numerous hash calculations to obtain a value below the difficulty threshold to generate a new block and obtain rewards. As the difficulty of mining increases, pools may develop competition strategies to reduce time and increase the rewards for mining blocks. This study investigates these strategies by examining whether mining pools in an alliance can perform selective broadcasting, hold mined blocks, and impose fork attacks. We developed algorithms to conduct simulation solutions based on the consensus mechanism of the Bitcoin operation, except for the hash function execution. The calculation results are replaced with two types of balls that represent hash values that satisfy the threshold of the mined block. The simulation algorithms were validated by comparing them with the expected average mining times. The results revealed a bias of less than 4%. Twelve simulation cases with various holding thresholds, holding periods, and forks for strategic alliance mining pools were simulated and evaluated. The results show that the mining rates of alliance mining pools increase, which means that the reward increases. The effects of these strategies on the winning rate reached 21.77% when the top three mining pools were constructed as alliances with withholding and imposing fork strategies. The effect of the average mining time is evaluated for mining pools with the same computing power distribution as practical mining pools for the Bitcoin system.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】Blockchains; Bitcoin; Consensus protocol; Broadcasting; Proof of Work; Games; Urban areas; Uncertainty; Timing; Throughput; Alliance; blockchain; fork; holding threshold; mining pool; mining difficulty; proof-of-work
【发表时间】2025
【收录时间】2025-02-19
【文献类型】
【影响因子】3.476
【主题类别】
--
【Abstract】Bibliometric analysis, a quantitative tool, assesses research trends, impacts, and interrelationships within a given field. Using data from the Web of Science, this research provides a thorough bibliometric examination of agent-based cybersecurity systems. We explore the motivation and significance of studying agent-based systems in cybersecurity, along with an overview of the existing literature. Using tools such as VOSviewer and Biblioshiny, we examine the growth and focus areas of publications over time, identify top contributors, and analyze collaboration patterns. The study also looks at the evolution of citation dynamics, their impact on field development, and thematic clusters of research topics. We identify major themes and their linkages, visually connecting frequently used phrases to create a hierarchical representation of the research landscape. Significant contributions at the intersection of agent-based systems and cybersecurity are emphasized. Our findings highlight growing trends, major research areas, and collaboration networks in the field. Key statistical findings show that publications on agent-based systems and cybersecurity have steadily increased since 2013, culminating in 2023 with over 1,200. Citations also peaked in 2023, at over 30,000. The top category, Computer Science Information Systems (1,424 publications), emphasizes the expanding importance of information security and artificial intelligence. Research articles are the most common document type (6,441). China is the largest contributor, followed by the US and India. Collaboration is prevalent, with important writers such as Zhang Y and Wang J driving cross-disciplinary research in fields like reinforcement learning and blockchain. To the best of our knowledge, this is the first work to conduct a comprehensive bibliometric analysis entirely focused on the intersection of agent-based systems and cybersecurity.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】Computer security; Security; Bibliometrics; Market research; Collaboration; Analytical models; Computer crime; Agent-based modeling; Monitoring; Malware; Agent-based systems; security; cybersecurity; bibliometric analysis
【发表时间】2025
【收录时间】2025-02-19
【文献类型】
【影响因子】3.418
【主题类别】
--
【Abstract】Efficiently managing virtual resources in the cloud is crucial for successful recourse utilization. Scheduling is a vital technique used to manage Virtual Machines (VMs), enabling placement and migration between hosts located in the same or different data centers. Effective scheduling not only ensures better server consolidation but also enhances hardware utilization and reduces power consumption in data centers. However, scheduling VMs across a Wide Area Network (WAN) poses considerable challenges due to connectivity issues, slower communication speeds, and concerns around data integrity and confidentiality. To enable informed scheduling decisions, it is critical to facilitate the exchange of real-time and accurate status information between cloud data centers, ensuring optimal resource allocation and minimizing latency. To address this, we propose a novel distributed cloud management solution that utilizes blockchain technology to facilitate efficient sharing of VM characteristics across multiple data centers. BigchainDB platform has been used as a blockchain-based ledger database to effectively share information required for VM scheduling and migration across different data centers. The proposed framework has been validated and compared with a Virtual Private Network (VPN)-based centralized management solution. The proposed model utilizing blockchain-based solution achieves 41.79% to 49.85% reduction in number of communication messages and 2% to 12% decrease in total communication delay comparing to the centralized model.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】VM scheduling; VM migration; Distributed management; Centralized management; Blockchain; BigchainDB
【发表时间】2025
【收录时间】2025-02-19
【文献类型】
【影响因子】3.399
【主题类别】
--
【Abstract】This study explores tail risk spillover between DeFi and Islamic assets using a time-frequency domain approach. We also conduct sub-sample analyses to account for the diverse impacts of COVID-19 and the Russian-Ukrainian conflict on financial markets. Recognizing the importance of global factors in financial market interdependencies, this research also assesses their impacts on tail risk connections. Empirical findings reveal varying levels of total connectedness among DeFi assets, sukuk markets, and Islamic equity indexes across different time spans, indicating a moderate but fluctuating degree of integration. DeFi assets generally appear disconnected from sukuk and Islamic stock markets over various periods, with the notable exception of a strong and consistent link between SNX in the DeFi sector and sukuk markets (excluding the Indonesian market) over medium- and long-term durations, suggesting that both DeFi and Islamic assets have hedging capabilities. Additionally, the integration between DeFi and Islamic assets is weaker during the COVID-19 era compared to the Russian-Ukrainian conflict period, with changes in the transmission mechanism. Further analysis identifies several potential predictors of tail risk connectedness between DeFi and Islamic assets. Our findings have significant risk management implications for investors and DeFi companies.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】DeFi; Islamic assets; Tail risk; Uncertainty factors; TVP-VAR
【发表时间】2025
【收录时间】2025-02-19
【文献类型】
【Author】 Garfinkel, Jon A. Hsiao, Lawrence Hu, Danqi
【影响因子】3.391
【主题类别】
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【Abstract】We present the first evidence of investor-trading-based disagreement's influence on cross-sectional cryptocurrency daily returns. We interpret abnormal trading volume as investor disagreement and find evidence in support of Miller's disagreement model: when short-sale constraints are binding, high abnormal volume (high disagreement) assets experience lower future returns. Further supporting Miller, these same conditions associate with higher contemporaneous order imbalance, and ex post decreases in both buying and selling activities, with the former exceeding the latter in magnitude. By contrast, the effect of high disagreement disappears after a coin's margin trading is activated. We conclude that price-optimism models explain the disagreement-returns relationship when opinion divergence is likely the dominant determinant of returns.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】
【发表时间】2025
【收录时间】2025-02-19
【文献类型】
【DOI】 10.1111/fima.12491
【影响因子】3.310
【主题类别】
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【Abstract】Energy management inside a blockchain framework developed for smart grids is primarily concerned with improving intrusion detection to protect data privacy. The emphasis is on real-time detection of cyberattacks and preemptive forecasting of possible risks, especially in the realm of electricity theft within smart grid systems. Existing Electricity Theft Detection techniques for smart grids have obstacles such as class imbalance, which leads to poor generalization, increased complexity due to large EC data aspects, and a high false positive rate in supervised models, resulting in incorrect classification of regular customers as abnormal. To provide security in the smart grid, a novel BLS Privacy Blockchain with Siamese Bi-LSTM is proposed. Initially, the privacy-preserving Boneh-Lynn-Shacham blockchain technique is built on BLS Short signature and hash algorithms, which mitigate misclassification rates and false positives in the detection of smart grid attacks. Then, a hybrid framework employs an intrusion detection algorithm based on Siamese Bidirectional Long Short-Term Memory to semantically distinguish between harmful and authentic behaviors, thereby improving data quality and predictive capabilities. Furthermore, a Recurrent Neural Network-Generative Adversarial Network is presented for detecting electricity fraud, which addresses the issue of class imbalance. This uses both supervised and unsupervised loss functions to produce synthetic theft samples that closely resemble actual theft incidents. From the experiment, it is showing that the proposed models perform with high accuracy and low error rates. The proposed model from the outcomes when compared to other existing models achieves high accuracy, detection rate, recall, and low computation time.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】deep blockchain framework; energy theft detection; generative adversarial networks; recurrent neural networks; Siamese bidirectional long short-term memory
【发表时间】2025
【收录时间】2025-02-19
【文献类型】
【DOI】 10.1002/ett.70033
【影响因子】3.310
【主题类别】
--
【Abstract】The Internet of Things (IoT) is transforming numerous sectors but also presents unique security challenges due to its interconnected and resource-constrained devices. This study introduces the Bidirectional Gaussian Hummingbird Optimized End-to-End Blockchain (BGHO-E2EB) model, designed to detect and classify cyberattacks within IoT environments. Unlike preventive approaches, the developed model focuses on real-time detection and categorization of attacks, enabling timely responses to emerging threats. The proposed model integrates blockchain technology through Ethereum-based smart contracts to enhance the security and integrity of data exchanges within IoT networks. Additionally, a Gaussian Artificial Hummingbird Algorithm is employed for optimal feature selection, minimizing data dimensionality and computational load. A Bidirectional Long Short-Term Memory (Bi-LSTM) network further improves the model's capability by accurately detecting and categorizing cyber threats based on selected features. The Adam optimizer is used for efficient parameter tuning within the Bi-LSTM network, ensuring high-performance cyberattack detection. The proposed model was evaluated using established IoT security benchmarks, including the UNSW-NB15, BOT-IoT, and NSL-KDD datasets, accomplishing an accuracy of 98.7%, precision of 96.3%, and security level of 99.5%, significantly outperforming traditional methods. These results demonstrate the effectiveness of BGHO-E2EB as a robust tool for detecting and classifying cyberattacks in IoT networks, making it suitable for real-world deployment in dynamic IoT environments where security is paramount.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】Adam optimization; bidirectional long short term memory; blockchain; cyberattack detection; end-to-end encryption; Gaussian artificial hummingbird optimization; smart contract
【发表时间】2025
【收录时间】2025-02-19
【文献类型】
【DOI】 10.1002/ett.70037
【影响因子】3.018
【主题类别】
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【Abstract】PurposeThis study aims to explore the innovative governance structures enabled by blockchain-based decentralized autonomous organizations (DAOs) in the context of international business (IB). As nonhierarchical entities managed through collective voting and peer-to-peer interactions, DAOs challenge traditional assumptions of multinational corporation (MNC) governance.Design/methodology/approachThe authors perform a literature review, which combines qualitative content analysis of both academic papers on DAO and whitepapers with quantitative analysis of bibliometrics using VosViewer.FindingsThe findings highlight DAOs' ability to generate new research questions and offer a foundation for future studies on decentralized governance in IB. Through a bibliometric analysis of 73 papers from Web of Science and qualitative content analysis, the authors identify four primary research streams in the DAO literature. A deep dive into financial DAOs, or DeFi DAOs, reveals insights into their governance mechanisms and implications for the studies in the field of IB.Research limitations/implicationsResearch on DAOs is in its early stages, and the practice in IB is nascent. As the regulatory, economic and technological landscape for DAOs changes, more research will be needed on the governance mechanisms and their sustainability.Originality/valueThis paper advances the field by providing a multilevel analysis of DAOs' potential impact on IB, considering macro (country), meso (MNC/DPE) and micro (multicultural team and individual) levels.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】Decentralized autonomous organizations; DAO; Blockchain; Bibliometric analysis; Smart contracts; Decentralized finance; International business
【发表时间】2025
【收录时间】2025-02-19
【文献类型】
【DOI】 10.1108/MBR-07-2024-0132
【影响因子】2.928
【主题类别】
--
【Abstract】Blockchain Technology (BCT) is the backbone of the next generation of the internet and thus affects how electronic business (e-business) is conducted. While the usage of BCT for the initiation and transaction phases in e-business has been studied, the negotiation aspect has not been considered in a comprehensive manner. The current literature on the utilisation of BCT in electronic negotiations (e-negotiations) primarily focuses on autonomous agents and lacks research on the support of e-negotiations conducted by human negotiators using negotiation support systems (NSSs). This results in the issue that the consequences of a transition to Web3.0-based NSSs are unclear, while other areas of e-business already apply Web3.0 technologies. We address this lack of knowledge following a design-oriented approach in three steps exploring the opportunities and challenges of using BCT for e-negotiations via NSSs. Firstly, the well-established negotiation support system Negoisst is extended by BCT features resulting in the development of a Web3.0-based NSS called NegoisstBCT to demonstrate the technical feasibility of this approach. Secondly, the potential opportunities and challenges of a Blockchain-based NSS are analysed referring to its technical architecture. Thirdly, a generalised view of the application of Web3.0-based NSSs in different settings is taken, discussing future research on BCT in e-negotiations. The present research thus fosters the application of Blockchain-based NSSs in e-negotiations and of NSSs in BCT application areas.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】Blockchain technology; Web3.0; dApp; Electronic negotiation; Negotiation support system
【发表时间】2025
【收录时间】2025-02-19
【文献类型】
【Author】 Xing, Yunfei Zhang, Justin Zuopeng
【影响因子】2.462
【主题类别】
--
【Abstract】The Metaverse represents a collaborative virtual realm blending physical and digital realities, fostering limitless avenues for online interaction, discovery and innovation. As technological strides propel immersive virtual worlds to the forefront of social media platforms, scholarly interest in the Metaverse surges, prompting extensive discourse. Drawing from social identity theory, this article introduces a novel framework for analysing online polarisation within discussions on the Metaverse, specifically on X (Twitter). Leveraging a multifaceted approach that integrates clustering, social network analysis, and text mining, our study delves into both group and opinion polarisation dynamics surrounding the Metaverse. Our findings uncover distinct community divisions and network structures, shedding light on prevalent themes, such as 'Non-Fungible Token (NFTs)', 'Virtual Products and Collections', 'Blockchain Technology', 'Gaming', and 'Financial Markets' that resonate within the public discourse.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】Group polarisation; Metaverse; online opinion; online polarisation; social identity; social media
【发表时间】2025
【收录时间】2025-02-19
【文献类型】
【Author】 Liu, Yang
【影响因子】2.449
【主题类别】
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【Abstract】This study explores food safety law research using the Latent Dirichlet Allocation (LDA) model, analyzing 2540 papers from the Web of Science (1996-2024). Nine key themes were identified: Public Health and Food Safety, Health Management and Supply Chain, Implementation Strategies and Consumer Rights, Behavior and Policy Regulation, Welfare and Impact Assessment, Purchasing Patterns and Product Performance, Food Industry Regulations and Control Measures, Sectoral Support and Risk Assessment, and Agricultural Systems and Environmental Concerns. The latter theme received the most attention, highlighting a focus on sustainable agriculture and environmental stewardship. The study notes a decline in research on Health Management and Supply Chain and Implementation Strategies and Consumer Rights, possibly due to their maturation or the rising importance of environmental issues. Secondary analysis of Agricultural Systems and Environmental Concerns revealed an interdisciplinary nexus of chemistry, environment, and health. Geographical analysis showed diverse national priorities: Australia and Japan emphasized regulatory and consumer themes, while France and India prioritized agricultural sustainability. High entropy values in China and the U.S. indicated broad research themes, while lower entropy in Azerbaijan and Bulgaria reflected concentrated focus. The findings offer actionable recommendations tailored to stakeholders. Policymakers should prioritize adaptive regulations that address emerging health threats and integrate real-time data systems. Industry professionals are encouraged to adopt advanced technologies, such as blockchain and AI, to enhance food safety and traceability. Researchers are advised to explore intersections between food safety, public health, and environmental sustainability to inform evidence-based policy reforms. These steps aim to address global challenges, promote public health, and ensure resilient food systems.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】food safety law; latent Dirichlet allocation; topic distribution; topic modeling; trend analysis
【发表时间】2025
【收录时间】2025-02-19
【文献类型】
【DOI】 10.1111/jfs.70009
【Author】 Huang, Jing Liu, Jingxian Yang, Wensheng
【影响因子】2.352
【主题类别】
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【Abstract】PurposeInventory pledge financing (IPF) serves as an effective means to address the financial constraints faced by supply chains. This study develops an IPF system involving a bank, SMEs and a third-party logistics provider (3PL) to explore the impact of varying cost structures and regulatory environments, specifically the strategic interactions within IPF system before and after the blockchain implementation. Also, provides theoretical foundations for improving the overall efficiency of financing and advancing the application of blockchain technology.Design/methodology/approachAn evolutionary game framework is employed to analyze the dynamics of financing behaviors before and after the blockchain implementation. Simulation methods are utilized to examine how different factors, including concealing costs, penalty structures and disposal prices, influence decision-making processes within IPF system.FindingsUnder IPF, the interactions of participants are shaped by asset management capabilities, reinvestment returns and penalties for fraud. As concealing costs increase, the likelihood of reaching a (loose regulation, compliant pledge) equilibrium rises. Post-blockchain implementation (IPFB), the equilibrium is influenced by default losses and compliance gains. Blockchain technology enhances regulation, effectively reducing fraud risks.Originality/valueThis study bridges significant gaps by offering a dynamic and behavioral perspective on IPF in the context of blockchain technology. Using an evolutionary game framework, the study uncovers how blockchain reshapes decision-making processes, mitigates fraud risks and enhances regulatory efficiency. By integrating cost structures and compliance incentives, it offers novel insights into behavioral shifts and systemic improvements in financing ecosystems.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】Inventory pledge financing; Blockchain technology; Evolutionary game; Collusion
【发表时间】2025
【收录时间】2025-02-19
【文献类型】
【DOI】 10.1108/K-10-2024-2736
【影响因子】2.350
【主题类别】
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【Abstract】This study clarifies discrepancies in previous research on the contribution of regulated Bitcoin futures to price discovery, where conclusions have varied between futures leading over spot markets or vice versa. We identify potential reasons behind these conflicting findings, including the choice of price discovery measures, sampling frequencies, modeling windows, futures contracts, and spot exchanges. Using 1-s sampling frequencies to accurately capture price discovery in the fast-paced markets and accounting for substantial noise differences between spot and futures markets, we find that the futures market generally leads spot markets, though this price leadership exhibits daily fluctuations. Moreover, we observe a pronounced increase in the futures market's contribution to price discovery around macroeconomic surprises and Tether stablecoin minting tweets.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】bitcoin; cryptocurrency; futures market; information releases; information shares; microstructure noise; price discovery
【发表时间】2025
【收录时间】2025-02-19
【文献类型】
【DOI】 10.1002/fut.22560
【Author】 Aytas, Murat Karaviran, Ceren
【影响因子】2.032
【主题类别】
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【Abstract】With the rapid advancement of technology, the transformation of images into digital codes has enabled computer technologies and their derivatives to be included in the art environment, production, and exhibition methods, as well as traditional tools used in artworks. Blockchain and NFT technology, which emerged because of these developments, merged with art to create a new digital art field. This new technology offers new perspectives on the preservation, exhibition and evaluation of art and plays an important role in the digital art economy. The main problematic of this study is to develop an in-depth understanding of the rise of NFT (Non-Fungible Token) technology in the art world and how this new digital art form is perceived by virtual communities. The effects of NFT on the production, distribution, appropriation, and evaluation of artworks have provoked different reactions among artists and art lovers. This study aims to reveal the value, acceptance, and criticism of NFT art in virtual communities through a netnographic analysis. In this study, the perspectives of virtual communities on NFT were examined using a netnographic analysis method. For this purpose, forum sites such as Donan & imath;m Haber, R10, Reddit, Shift Delete and Technopat, which have high traffic and active members, were selected and the content shared on these sites between January and October in 2021, when NFT was popular, was analyzed. Discussions, comments, and opinions about NFT on these sites were analyzed in depth. As a result of the study, it was determined that NFT has received various reactions in the art world, some users find this technology meaningless and speculative, while others see NFT as a revolutionary step in the digitalization of art. It is concluded that NFT offers new opportunities to artists and collectors by securing the ownership, authenticity, and trade of artworks in a digital environment.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】NFT; NFT art; digital art; virtual communities; blokchain
【发表时间】2025
【收录时间】2025-02-19
【文献类型】
【Author】 Tian, Lihui Wu, Haifeng Xie, Qichang
【影响因子】1.681
【主题类别】
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【Abstract】This paper investigates the impact of FOMC announcements on cryptocurrency risk spillovers under different market conditions and their mechanisms of action. We calculate the high-frequency RGARCH volatilities of four major dirty cryptocurrencies and six major clean currencies, and apply the quantile-expanded joint-network approach to test their risk spillovers under different market conditions, and then investigate their impact and mechanism of action by monetary shocks. The results show that: (i) the total spillover in the extreme volatility market is larger than the total spillover in the normal market, and there is a tail asymmetry. (ii) The total cryptocurrency risk spillover in the highly volatile market, the normal market, and the smooth volatility market are all positively affected by monetary shocks. (iii) Mechanism analysis shows that the FOMC announcement will have an impact on the total cryptocurrency market risk spillover through two channels, which are changing the market expectations and hedging demand. Heterogeneity analysis shows that clean cryptocurrencies have positive net spillovers to dirty cryptocurrencies, and the mutual spillovers between the two are significantly affected by monetary shocks in extremely volatile markets.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】FOMC announcements; Dirty and clean cryptocurrencies; Cryptocurrency risk spillovers; Quantile expanded joint network; E58; G15; G23
【发表时间】2025
【收录时间】2025-02-19
【文献类型】
【影响因子】1.452
【主题类别】
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【Abstract】This paper examines the hourly downward/upward multifractality and dynamic efficiency of four cryptocurrencies-Bitcoin (BTC), Ethereum (ETH), Ripple (XRP), and Litecoin (LTC)- before and during the COVID-19 pandemic, and during the Russia-Ukraine tension. Using the asymmetric multifractal detrended fluctuation analysis method, the results show significant asymmetric multifractality in all series, which intensifies for BTC only throughout the COVID-19 crisis and narrows for ETH, XRP, and LTC. Moreover, we show that cryptocurrency markets are more inefficient during the upward (downward) trend and before (during) the COVID-19 crisis. LTC is the least inefficient market pre COVID-19, whereas XRP is the least inefficient during the pandemic crisis. The results show evidence of excessive asymmetric multifractality for all four crypto markets. Before the COVID-19 crisis, positive values of excess asymmetry in multifractality have been identified for BTC and LTC markets, whereas the excess asymmetry values were negative for ETH and XRP markets. BTC and ETH markets showed wider multifractality fluctuations compared to LTC and XRP, indicating a stronger reaction to the war's impact.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】asymmetric multifractality; COVID-19 pandemic; cryptocurrency markets; efficiency
【发表时间】2025
【收录时间】2025-02-19
【文献类型】
【DOI】 10.1111/1467-8454.12390
【Author】 Shao, Shi-Feng Cheng, Jinhua
【影响因子】1.287
【主题类别】
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【Abstract】For the development of the clean energy industry and the transformation of energy, clean energy metals are essential raw materials. They are also crucial constituents of the commodity market, attracting many cross-market investors. This research uses the asymmetric TVP-VAR framework to investigate the time-varying connectivity between cryptocurrency environmental attention (ICEA) and clean energy metals' prices. The results show that ICEA received the net spillover from clean energy metals, while clean energy metals exhibit heterogeneity. There is a difference between the spillover of positive and negative returns among series, and the connectedness of negative returns is more prominent. In addition, the series' total and net connectivity are time-varying and influenced by COVID-19. This study has certain reference values for the academia and market participants.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】Clean energy metals; environmental attention; cryptocurrency; asymmetric connectedness; TVP-VAR
【发表时间】2025
【收录时间】2025-02-19
【文献类型】
【影响因子】1.250
【主题类别】
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【Abstract】This study introduces a hierarchical energy management platform that leverages blockchain technology to eliminate the need for a centralized coordinator. The platform is designed to operate in energy communities facing stochastic uncertainties. The approach is divided into two levels: at the upper level where a stochastic distributed model predictive control problem is solved by all households in the community to determine control actions on an hourly basis. A smart contract serves as a bridge between households, performing control tasks and facilitating information exchange. In contrast, at the lower level, each household independently solves a model predictive control problem locally to track the references established after consensus is reached by the upper layer, at a much higher frequency. The effectiveness of the platform in optimizing the community's economic performance and adhering to probabilistic constraints is demonstrated through extensive simulations.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】Energy management and distribution systems; blockchain; stochastic control; model predictive control
【发表时间】2025
【收录时间】2025-02-19
【文献类型】
【DOI】 10.4995/riai.2024.21330
【Author】 Su, Zelin
【影响因子】1.037
【主题类别】
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【Abstract】Blockchain evidence is a technical method for evidence storage, transmission and fixation. Its evidential value has a dual nature, reflected in the fact that it cannot be absolutely tamper-resistant, can only provide periodic assurance of evidence authenticity and the commonly used consortium chains do not possess all the benefits of public chains. Simultaneously, blockchain evidence occupies a unique status within the entire evidence system, it serves as an evidentiary storage mechanism, is essentially an electronic evidence reflecting both the evidence collection process and outcome and its notarisation and forensic examination documents are a type of opinion evidence. It is evident that blockchain evidence does not emerge in a vacuum, rather than serving as a mere replacement for traditional evidence, blockchain evidence represents an upgrade in the functionality and effectiveness of traditional evidence. From this perspective, the improvement of blockchain evidence rules should align with the basic position of 'technological neutrality', which means that although technological evolution can lead to rapid changes, legislators are not always required to cater to these dynamic demands. It is essential to distinguish between on-chain and off-chain when addressing issues of authenticity, hearsay and originality, and improvements proposing should within the frameworks of existing electronic evidence rules and opinion evidence rules, thereby unlocking the potential of blockchain evidence.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】Blockchain evidence; depository mechanism; electronic evidence; opinion evidence; technological neutrality
【发表时间】2025
【收录时间】2025-02-19
【文献类型】
【影响因子】0.864
【主题类别】
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【Abstract】In Precision Agriculture (PA), the need to create a safe and intelligent building prompts the integration of blockchain technology with Internet of Things (IoT)-based systems. This paper proposes a deep reinforcement learning-based prediction and Blockchain-based Secure Data Sharing system for PA. The major objective is to apply blockchain technology to enable safe data sharing in the PA space. IoT sensors first collect data on important characteristics including weather, temperature, humidity, crop health, and soil moisture. Then, the collected data are pre-processed by z-score and Decimal Scaling normalization techniques. Then, the pre-processed data are analyzed and clustered by the Balance Iterative Reducing and Clustering utilizing Hierarchies (BIRCH) technique. It is a scalable and efficient algorithm for clustering large datasets. Next, the features are extracted by Convolutional Neural Networks (CNN). CNNs have independent feature learning and powerful computing ability, and it improves the accuracy and automation of extraction. After the feature extraction, the optimal features are selected by Hybrid Red Deer and Dwarf Mongoose Optimization (H-RDMO). For prediction, an Attention-based Recurrent Neural Network is utilized, which gives accurate predictions on sequential data and then the Hybrid Deep Reinforcement Learning approach (Hybrid deep Q-learning and policy gradient model) is used for the accurate disease classification. Finally, Hybrid Modified ECC with ElGamal encryption technique is used to ensure data security during sharing. It provides a robust and efficient cryptographic solution with enhanced security features. The suggested model is implemented using the PYTHON programming language, and its performance is assessed employing metrics such as F-score, recall, specificity, precision, sensitivity, accuracy, MCC, NPV, FPR, and FNR. Suggested optimized H-RDMO achieves higher accuracy (98.4%) and precision (97%) compared to current techniques and the ESMECC-Elg achieves the Energy consumption of 150 J.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】attention based RNN; data sharing; egret swarm optimization; IoT technology; precision agriculture
【发表时间】2025
【收录时间】2025-02-19
【文献类型】