【Author】 Liu, Ziming Huang, Bonan Li, Yushuai Sun, Qiuye Pedersen, Torben Bach Gao, David Wenzhong

【Source】IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS CCF-C

【影响因子】11.648

【主题类别】

区块链应用-实体经济-电力领域

【Abstract】The development of low-carbon power systems has not only elevated the investment costs of power enterprises, but also generated a vast amount of electricity data. The electricity data trading holds promising potential as a primary means to cover investment costs. However, there is a lack of research on the electricity data trading. To address this issue, this article designs an electricity data trading method based on price game and blockchain for low-carbon power systems. It encompasses a data trading framework and the corresponding trading mechanism. The proposed trading framework contains data providers, data consumers, and a blockchain-based information system that plays the role of the data servicer to handle the transactions between data providers and consumers. The proposed trading mechanism mainly consists of three parts: 1) valuation; 2) pricing; and 3) copyrights confirmation. Those parts are executed sequentially to complete the electricity data trading process from valuation to clearing. Specially, the information theory is employed to realize multidimensional electricity data valuation. Further, the data trading game pricing is formulated as a multiobjective optimization problem considering market power constraints to solve. In addition, the digital watermarking combined with blockchain is designed to protect the electricity data copyright. With those components, the designed electricity data trading method enables the power enterprises to make profit from the low-carbon smart energy systems. Finally, experiments demonstrate the effectiveness of the proposed method.

你可以尝试使用大模型来生成摘要 立即生成

【Keywords】Blockchain; data pricing; data valuation; electricity data trading; information theory

【发表时间】2024

【收录时间】2024-03-06

【文献类型】 实证数据

【DOI】 10.1109/TII.2023.3345450

【Author】 Guo, Hao Meese, Collin Li, Wanxin Shen, Chien-Chung Nejad, Mark

【Source】IEEE TRANSACTIONS ON SERVICES COMPUTING CCF-A

【影响因子】11.019

【主题类别】

区块链技术-协同技术-联邦学习

【Abstract】Federated Learning (FL) is a privacy-preserving machine learning (ML) technology that enables collaborative training and learning of a global ML model based on aggregating distributed local model updates. However, security and privacy guarantees could be compromised due to malicious participants and the centralized FL server. This article proposed a bi-level blockchained architecture for secure federated learning-based traffic prediction. The bottom and top layer blockchain store the local model and global aggregated parameters accordingly, and the distributed homomorphic-encrypted federated averaging (DHFA) scheme addresses the secure computation problems. We propose the partial private key distribution protocol and a partially homomorphic encryption/decryption scheme to achieve the distributed privacy-preserving federated averaging model. We conduct extensive experiments to measure the running time of DHFA operations, quantify the read and write performance of the blockchain network, and elucidate the impacts of varying regional group sizes and model complexities on the resulting prediction accuracy for the online traffic flow prediction task. The results indicate that the proposed system can facilitate secure and decentralized federated learning for real-world traffic prediction tasks.

你可以尝试使用大模型来生成摘要 立即生成

【Keywords】Blockchain; federated learning; traffic prediction; secure averaging; homomorphic encryption

【发表时间】2023

【收录时间】2024-03-06

【文献类型】 实验仿真

【DOI】 10.1109/TSC.2023.3318990

【Author】 Tang, Bingxin Liang, Junyuan Cai, Zhongteng Cai, Ting Zhou, Xiaocong Chen, Yingye

【Source】IEEE TRANSACTIONS ON SERVICES COMPUTING CCF-A

【影响因子】11.019

【主题类别】

区块链技术-协同技术-深度学习

【Abstract】Blockchain-based cryptocurrencies have developed rapidly in recent years, however, scalability is one of the biggest challenge. Payment channel networks (PCNs) are one of the important solutions to blockchain scalability and routing is the most critical problem in PCN. Routing algorithms in PCNs have evolved fast and achieved high throughput. However, most of these routing algorithms are designed from the perspective of technical feasibility, and few algorithms focus on the incentives of each off-chain participant, especially the economic incentives for intermediate routing nodes. Besides, due to the highly dynamic nature of off-chain channel deposits, existing routing algorithms rely heavily on channel deposit probing in order to ensure high throughput. In this article, we design routing algorithms from an incentive perspective to improve the profit of intermediate nodes and use deep learning to reduce the dependency of off-chain routing on channel deposit probing. Our experiments show that under the same model, MDRL-IR can increase the profit of intermediate nodes by up to 1.87x and increase the throughput by up to 2.0x compared to the state-of-the-art routing algorithm, while ensuring that the user routing cost per unit throughput remains unchanged. Moreover, approximate performance can be achieved when deposit probing is greatly reduced.

你可以尝试使用大模型来生成摘要 立即生成

【Keywords】Blockchain scalability; channel balance; deep reinforcement learning; incentivize; PCN routing

【发表时间】2023

【收录时间】2024-03-06

【文献类型】 实验仿真

【DOI】 10.1109/TSC.2023.3323647

【Author】 Kim, Ryeong Hwan Song, Hwangjun Park, Gi Seok

【Source】IEEE TRANSACTIONS ON SERVICES COMPUTING CCF-A

【影响因子】11.019

【主题类别】

区块链应用-虚拟经济-Web3

【Abstract】Web 3.0 is an emerging Internet paradigm based predominantly on the blockchain technology. Because Web 3.0 applications are designed to operate over trustless and permissionless networks, they can have significant advantages, such as decentralized control structures and transparency. Hence, existing web applications are being reproduced using Web 3.0 technologies. In contrast, real-time services are still implemented with the Web 2.0 architecture. In particular, implementing Web 3.0 media streaming requires modifications to the service architecture of existing media streaming systems because some technical difficulties exist. For example, as data moves from centralized data centers to distributed storage, the user's quality of experience may be severely degraded. In addition, the software components comprising the Web 3.0 stack, such as interplanetary file system, cryptocurrency wallets, and the Ethereum JavaScript API are not compatible with various combinations of OSs, media players, and browsers. Therefore, in this study, we propose an end-to-end system architecture designed for Web 3.0 real-time services, which prevents degradation of service quality. Further, we present a media NFT marketplace named Retriever (https://retriever.live) fully developed using Web 3.0 technologies. Retriever allows users to enjoy watching video content and further to directly trade their content without intermediaries by ensuring the privacy of the data and managing digital intellectual property. In particular, Retriever does not sacrifice the user experience and is compatible with multiple mobile devices.

你可以尝试使用大模型来生成摘要 立即生成

【Keywords】Web 3.0; blockchain; non-fungible token (NFT); InterPlanetary file system (IPFS); real-time services

【发表时间】2023

【收录时间】2024-03-06

【文献类型】 综述

【DOI】 10.1109/TSC.2023.3307153

【Author】 Hammoud, Ahmad Mizouni, Rabeb Otrok, Hadi Singh, Shakti Mourad, Azzam Dziong, Zbigniew

【Source】IEEE TRANSACTIONS ON SERVICES COMPUTING CCF-A

【影响因子】11.019

【主题类别】

区块链技术-协同技术-雾计算

【Abstract】Fog computing empowers the internet of vehicles (IoV) paradigm by offering computational resources near the end users. In this dynamic paradigm, users tend to move in and out of the range of fog nodes which has implications for the quality of service of the vehicular applications. To cope with these limitations, scholars addressed forming federations of fog providers for task offloading purposes. Nonetheless, a few challenges remain a burden for the formation of the federations. The formation mechanisms used to structure the federations of providers are still not fully stable. This causes a problem because a structureless federation can lead to an underperforming infrastructure. Furthermore, most of the literature ignored the honesty metrics of the providers and how trustworthy they are in allocating the agreed-upon resources for processing the tasks. Moreover, adopting a central reputation mechanism is questionable in terms of reliability due to many complications including the lack of consensus. In this work, we develop a Blockchain-based reputation mechanism for assisting the formation of fog federations for IoV applications. Our mechanism comprises on-chain smart contracts for storing and manipulating the providers' reputations, and an off-chain Hedonic-based formation process that considers the parameters extracted from the chain to build the federations. We develop smart contracts using Solidity and deploy them on the Ethereum Blockchain. We test our mechanism using the EUA dataset as a proof of concept and compare it to other works in the literature. The results obtained show that our approach is able to enhance the overall payoff and quality of service in the IoV paradigm.

你可以尝试使用大模型来生成摘要 立即生成

【Keywords】Fog federations; blockchain; Ethereum; Internet of Vehicles; game theory

【发表时间】2023

【收录时间】2024-03-06

【文献类型】 实证数据

【DOI】 10.1109/TSC.2023.3324734

【Author】 Zhang, Duo Wang, Shangping Zhang, Qian Zhang, Yaling

【Source】IEEE TRANSACTIONS ON SERVICES COMPUTING CCF-A

【影响因子】11.019

【主题类别】

区块链应用-实体经济-支付领域

【Abstract】Cloud computing has brought great convenience to data storage and resource sharing, however, there are still concerns about data security and service quality. Attribute-based encryption (ABE) and searchable encryption (SE) are always adopted to achieve data access authorization and data retrieval on encrypted data in data sharing, respectively. But more efficient and accurate methods have been always pursued. Moreover, the spoofing attack is another important aspect that raises concerns, especially when it comes to reliability of search results and online payments. Blockchain, an emerging technology that can be used to solve the problem of trust, has shown great application potential in finance and data sharing. Based on blockchain, we propose an attribute-based conjunctive keyword search (ABCKS) scheme with verifiability and fairness. In this paper, data privacy-preserving, fine-grained access control, and multi-keywords search can be supported simultaneously. Blockchain and smart contract are employed to facilitate the search result verification process and ensure fair payment in the trustless case. Furthermore, we reduce the user's decryption load to a constant level by performing partial decryption on the cloud side. Finally, the results of the performance evaluation indicate that our scheme has higher efficiency and security.

你可以尝试使用大模型来生成摘要 立即生成

【Keywords】Blockchain; attribute-based encryption; fine-grained access control; conjunctive keyword search; smart contract

【发表时间】2023

【收录时间】2024-03-06

【文献类型】 实验仿真

【DOI】 10.1109/TSC.2023.3311877

【Author】 de l'Etang, Filezac

【Source】FINANCE RESEARCH LETTERS

【影响因子】9.848

【主题类别】

区块链治理-市场治理-稳定币

【Abstract】Investigating the impact of heterogeneous announcements on stablecoin transaction volumes, an event study is conducted on stablecoins using intraday data. The assumption is that the backed-asset creates a channel through which announcements exert an effect on cryptocurrency transaction volumes. Results indicate that decentralized stablecoins are more sensitive to institutional announcements than both USDC and USDT, suggesting potential policy implications as international coordination or monitoring. The media are found to be worth watching concerning USDT and can play an active role in shaping trading volume over a short time period.

你可以尝试使用大模型来生成摘要 立即生成

【Keywords】Stablecoin; Transaction volumes; Event study policy implications institutions,; media decentralize

【发表时间】2024

【收录时间】2024-03-06

【文献类型】 实证数据

【DOI】 10.1016/j.frl.2024.104999

【Author】 Shanan, Tamir Narotzki, Doron

【Source】FINANCE RESEARCH LETTERS

【影响因子】9.848

【主题类别】

区块链治理-市场治理-区块链金融监管

【Abstract】In this paper we look into the history of cryptographic assets and its evolution, analyze the relevant tax framework and identify the issues with regard to cryptographic assets, and suggest a new regulatory framework for such assets that would allow governments to tax these assets more efficiently while at the same time not hold back the technological development and evolution of cryptographic assets.

你可以尝试使用大模型来生成摘要 立即生成

【Keywords】Crypto; Cryptographic assets; Bitcoin; Tax

【发表时间】2024

【收录时间】2024-03-06

【文献类型】 综述

【DOI】 10.1016/j.frl.2024.105018

【Author】 Montakhabi, Mehdi Madhusudan, Akash Mustafa, Mustafa A. Vanhaverbeke, Wim Almirall, Esteve van der Graaf, Shenja

【Source】BIG DATA & SOCIETY

【影响因子】8.731

【主题类别】

区块链应用-实体经济-能源领域

【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】2024-03-06

【文献类型】 编辑社论

【DOI】 10.1177/20539517231223863

【Author】 Liu, Zhaowei Wang, Yixian Wang, Shenqiang Zhao, Xiangfu Wang, Haiyang Yin, Haoyu

【Source】EXPERT SYSTEMS WITH APPLICATIONS CCF-C

【影响因子】8.665

【主题类别】

区块链治理-技术治理-异常检测

【Abstract】In recent years, heterogeneous graph neural networks have been applied to the analysis of complex networks, and in ethereum transaction, fraudsters disguise themselves as normal transaction accounts through their behavior, increasing the fault tolerance of using heterogeneous graph neural networks. This paper proposes a heterogeneous graph neural network approach based on neighbor filtering to identify fraudulent ethereum accounts. Specifically, firstly, the collected data of all 386612 ethereum transactions are constructed as transaction subsets G1, G2 and G3. Then, to measure the similarity between ethereum transaction accounts, this paper proposes a similarity measure based on random walks and uses reinforcement learning to find the best neighbor for each relation in the heterogeneous network, and aggregation within and between relations to represent the neighborhood relationship between neighboring nodes. To solve the overfitting problem of inter-relationship aggregation, this paper adds initial residuals to inter-relationship aggregation so that the neighbor aggregation process can be applied to deeper GNNs, resulting in a 2% increase in the AUC metric, which is important for the effective identification of ethereum identities.

你可以尝试使用大模型来生成摘要 立即生成

【Keywords】Heterogeneous graphs neural networks; Ethereum identity; Transactions network

【发表时间】2024

【收录时间】2024-03-06

【文献类型】 实验仿真

【DOI】 10.1016/j.eswa.2023.122489

【Author】 Bouteska, Ahmed Abedin, Mohammad Zoynul Hajek, Petr Yuan, Kunpeng

【Source】INTERNATIONAL REVIEW OF FINANCIAL ANALYSIS

【影响因子】8.235

【主题类别】

区块链治理-市场治理-价格预测

【Abstract】Cryptocurrency price forecasting is attracting considerable interest due to its crucial decision support role in investment strategies. Large fluctuations in non-stationary cryptocurrency prices motivate the urgent need for accurate forecasting models. The lack of seasonal effects and the need to meet a number of unrealistic re-quirements make it difficult to make accurate forecasts using traditional statistical methods, leaving machine learning, particularly ensemble and deep learning, as the best technology in the area of cryptocurrency price forecasting. This is the first work to provide a comprehensive comparative analysis of ensemble learning and deep learning forecasting models, examining their relative performance on various cryptocurrencies (Bitcoin, Ethereum, Ripple, and Litecoin) and exploring their potential trading applications. The results of this study reveal that gated recurrent unit, simple recurrent neural network, and LightGBM methods outperform other machine learning methods, as well as the naive buy-and-hold and random walk strategies. This can effectively guide investors in the cryptocurrency markets.

你可以尝试使用大模型来生成摘要 立即生成

【Keywords】Cryptocurrency; Bitcoin; Forecasting; Ensemble learning; Deep learning; Neural networks

【发表时间】2024

【收录时间】2024-03-06

【文献类型】 实证数据

【DOI】 10.1016/j.irfa.2023.103055

【Author】 Yang, Xianqi Gao, Qing Basin, Michael V. Li, Hao Peng, Xin

【Source】INFORMATION SCIENCES CCF-B

【影响因子】8.233

【主题类别】

区块链应用-实体经济-工业互联网

【Abstract】In modern manufacturing industries, industrial components are becoming increasingly open and interconnected which significantly promotes the collaboration capability and producing efficiency on one hand, while, on the other hand, makes the industrial internet more vulnerable to various threats and attacks. In order to defend a distributed industrial Internet network system against two kinds of typical mutinous attacks, i.e., Byzantine attacks and DDoS attacks, that happen inside of the system, this paper proposes an Ethereum-based securing strategy. First, a credit mechanismbased Bayesian inference method is developed to increase the system nodes' sensitivity to malicious behavior and to improve system's robustness against false messages. Then, a miner selection method is proposed to avoid the information clog occurring in the system nodes' txpools and improve the efficiency of the whole system. The constructed securing strategy consists of these two methods and is shown to be applicable to industrial scenarios involving both mobile and static nodes. Several simulations are presented to verify effectiveness of the proposed approach. It is found that the accuracy of identifying false messages broadcast by Byzantine attackers is about 90%.

你可以尝试使用大模型来生成摘要 立即生成

【Keywords】Ethereum; Industrial security; Industrial Internet; Miner selection; Credit mechanism

【发表时间】2024

【收录时间】2024-03-06

【文献类型】 实验仿真

【DOI】 10.1016/j.ins.2023.119904

【Author】 Xiao, Ke Li, Jiayang He, Yunhua Wang, Xu Wang, Chao

【Source】FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE

【影响因子】7.307

【主题类别】

区块链应用-实体经济-支付领域

【Abstract】With the increasing demand for digital currencies and other blockchain transactions, the contradiction between the growing demand and the limited blockchain space has become increasingly prominent, and the scalability of the blockchain urgently needs to be resolved. The existing off -chain payment channel solutions do not give enough consideration to the multi -party parallel transaction process, and the transaction process lacks supervision, making it difficult to meet the actual demand. In this paper, we propose a multi -party secure, flexible, concurrent and supervisable off -chain payment channel scheme. Our scheme not only optimizes the current transaction process so that the participants and channel balance within the channel can be flexibly changed without affecting the normal transaction process, but also designs a multi -level collaborative supervision mechanism from multiple perspectives of positive and negative, active and passive, and multiple layers of on -chain and off -chain to ensure the safety and convenience of the transaction process. The security of the scheme was also analyzed, especially the possible collusion in the channel. We simulated the operation of the channel in the blockchain simulation and testing software Simblock and tested the scheme from various aspects. The experiments show that our scheme is able to achieve secure supervision within the channel with a modest overhead (about 15%). Testing of the mentioned smart contracts further illustrates the feasibility of the scheme.

你可以尝试使用大模型来生成摘要 立即生成

【Keywords】Blockchain; Supervision; Payment channel; Smart contract; Off-chain transaction; Scalability

【发表时间】2024

【收录时间】2024-03-06

【文献类型】 实验仿真

【DOI】 10.1016/j.future.2024.01.012

【Author】 Vern, Priyanka Panghal, Anupama Mor, Rahul S. Kamble, Sachin S. Islam, Md. Shamimul Khan, Syed Abdul Rehman

【Source】OPERATIONS MANAGEMENT RESEARCH

【影响因子】7.032

【主题类别】

区块链应用-实体经济-食品供应链

【Abstract】Blockchain technology offers undeniable benefits of enhanced transparency, reliability, and information accuracy to agri-food supply chains. Currently, the implementation of this technology has associated challenges. This paper explores the influential barriers to implementing blockchain technology (BCT) in the agri-food supply chain (AFSC). An integrated literature review approach and expert opinions were employed to explore the influential barriers. The barriers were modelled using the hybrid fuzzy-based decision-making trial and evaluation laboratory (Fuzzy-DEMATEL) approach to evaluate the interrelationship and classify them into cause-and-effect groups. As an outcome, a comprehensive framework was proposed revealing the unfamiliarity with technology, high investment cost, lack of regulations, technological infeasibility, and scalability as key influential barriers. This study will help the decision-makers to focus on influential barriers and identify the roadmap towards blockchain implementation.

你可以尝试使用大模型来生成摘要 立即生成

【Keywords】Blockchain technology; Agri-food supply chain; Influential barriers; Fuzzy-DEMATEL approach; Digital transformations

【发表时间】2023

【收录时间】2024-03-06

【文献类型】 综述

【DOI】 10.1007/s12063-023-00388-7

【Author】 Alamaren, Amro Saleem Gokmenoglu, Korhan K. Taspinar, Nigar

【Source】FINANCIAL INNOVATION

【影响因子】6.793

【主题类别】

区块链治理-市场治理-数字货币

【Abstract】This study investigates volatility spillovers and network connectedness among four cryptocurrencies (Bitcoin, Ethereum, Tether, and BNB coin), four energy companies (Exxon Mobil, Chevron, ConocoPhillips, and Nextera Energy), and four mega-technology companies (Apple, Microsoft, Alphabet, and Amazon) in the US. We analyze data for the period November 15, 2017-October 28, 2022 using methodologies in Diebold and Yilmaz (Int J Forecast 28(1):57-66, 2012) and Barunik and Krehlik (J Financ Economet 16(2):271-296 2018). Our analysis shows the COVID-19 pandemic amplified volatility spillovers, thereby intensifying the impact of financial contagion between markets. This finding indicates the impact of the pandemic on the US economy heightened risk transmission across markets. Moreover, we show that Bitcoin, Ethereum, Chevron, ConocoPhilips, Apple, and Microsoft are net volatility transmitters, while Tether, BNB, Exxon Mobil, Nextera Energy, Alphabet, and Amazon are net receivers Our results suggest that short-term volatility spillovers outweigh medium- and long-term spillovers, and that investors should be more concerned about short-term repercussions because they do not have enough time to act quickly to protect themselves from market risks when the US market is affected. Furthermore, in contrast to short-term dynamics, longer term patterns display superior hedging efficiency. The net-pairwise directional spillovers show that Alphabet and Amazon are the highest shock transmitters to other companies. The findings in this study have implications for both investors and policymakers.

你可以尝试使用大模型来生成摘要 立即生成

【Keywords】Volatility spillovers; Connectedness network; Cryptocurrency; Energy companies; Technology companies; C58; G10; And N70

【发表时间】2024

【收录时间】2024-03-06

【文献类型】 实证数据

【DOI】 10.1186/s40854-024-00626-2

【Author】 Trozze, Arianna Kleinberg, Bennett Davies, Toby

【Source】FINANCIAL INNOVATION

【影响因子】6.793

【主题类别】

区块链治理-技术治理-恶意合约检测

【Abstract】Decentralized Finance (DeFi) is a system of financial products and services built and delivered through smart contracts on various blockchains. In recent years, DeFi has gained popularity and market capitalization. However, it has also been connected to crime, particularly various types of securities violations. The lack of Know Your Customer requirements in DeFi poses challenges for governments trying to mitigate potential offenses. This study aims to determine whether this problem is suited to a machine learning approach, namely, whether we can identify DeFi projects potentially engaging in securities violations based on their tokens' smart contract code. We adapted prior works on detecting specific types of securities violations across Ethereum by building classifiers based on features extracted from DeFi projects' tokens' smart contract code (specifically, opcode-based features). Our final model was a random forest model that achieved an 80% F-1 score against a baseline of 50%. Notably, we further explored the code-based features that are the most important to our model's performance in more detail by analyzing tokens' Solidity code and conducting cosine similarity analyses. We found that one element of the code that our opcode-based features can capture is the implementation of the SafeMath library, although this does not account for the entirety of our features. Another contribution of our study is a new dataset, comprising (a) a verified ground truth dataset for tokens involved in securities violations and (b) a set of legitimate tokens from a reputable DeFi aggregator. This paper further discusses the potential use of a model like ours by prosecutors in enforcement efforts and connects it to a wider legal context.

你可以尝试使用大模型来生成摘要 立即生成

【Keywords】DeFi; Decentralized finance; Ethereum; Fraud; Cryptocurrency; Machine learning; Securities law

【发表时间】2024

【收录时间】2024-03-06

【文献类型】 实验仿真

【DOI】 10.1186/s40854-023-00572-5

【Author】 Hong, Hanshu Hu, Bing Sun, Zhixin

【Source】HUMAN-CENTRIC COMPUTING AND INFORMATION SCIENCES

【影响因子】6.558

【主题类别】

区块链技术-核心技术-共识机制

【Abstract】Internet of Things (IoT) connects physical entities to the Internet via various sensing devices and brings the network connection to all the people and objects in the world. Due to its inherent openness, however, the collected data in the IoT scenario are vulnerable to different types of attacks such as manipulation, forgery, etc. Therefore, the mobile crowdsensing platform needs to adopt extra security mechanisms to ensure the integrity of perceptual data. Blockchain is a promising technique for providing trustworthy data storage in the IoT data collection scenario, but the tamper resistance property of conventional blockchain gives rise to a problem, i.e., the incorrect data produced during the collection and transition cannot be modified in a timely manner. To solve the problem better, this paper proposes a secure editable consensus mechanism for the blockchain-based mobile crowdsensing scenario. Our scheme has the merits of blockchain and secret sharing theory to provide secure data storage along with the property of modifying the incorrect data blocks when necessary. We construct concrete algorithms of the consensus mechanism and prove its soundness under two security models. Based on the performance evaluation, our scheme is demonstrated to achieve multiple functional properties along with relatively low calculation burden.

你可以尝试使用大模型来生成摘要 立即生成

【Keywords】Blockchain; Consensus; Security; Efficiency

【发表时间】2024

【收录时间】2024-03-06

【文献类型】 实验仿真

【DOI】 10.22967/HCIS.2024.14.021

【Author】 Lin, Yijing Gao, Zhipeng Du, Hongyang Kang, Jiawen Niyato, Dusit Wang, Qian Ruan, Jingqing Wan, Shaohua

【Source】IEEE TRANSACTIONS ON COMMUNICATIONS CCF-B

【影响因子】6.166

【主题类别】

区块链技术-协同技术-联邦学习

【Abstract】Blockchain-based Federated Learning (FL) technology enables vehicles to make smart decisions, improving vehicular services and enhancing the driving experience through a secure and privacy-preserving manner in Intelligent Transportation Systems (ITS). Many existing works exploit two-layer blockchain-based FL frameworks consisting of a mainchain and subchains for data interactions among intelligent vehicles, which resolve the limited throughput issue of single blockchain-based vehicular networks. However, the existing two-layer frameworks still suffer from a) strong dependency on predetermined and fixed parameters of vehicular blockchains which limit blockchain throughput and reliability; and b) high communication costs incurred by interactions among intelligent vehicles between the mainchain and subchains. To address the above challenges, we first design an adaptive blockchain-enabled FL framework for ITS based on blockchain sharding to facilitate decentralized vehicular data flows among intelligent vehicles. A streamline-based shard transmission mechanism is proposed to ensure communication efficiency almost without compromising the FL accuracy. We further formulate the proposed framework and propose an adaptive sharding mechanism using Deep Reinforcement Learning to automate the selection of parameters of vehicular shards. Numerical results clearly show that the proposed framework and mechanisms achieve adaptive, communication-efficient, credible, and scalable data interactions among intelligent vehicles.

你可以尝试使用大模型来生成摘要 立即生成

【Keywords】Blockchain sharding; federated learning; reputation; deep reinforcement learning

【发表时间】2023

【收录时间】2024-03-06

【文献类型】 实验仿真

【DOI】 10.1109/TCOMM.2023.3288591

【Author】 Zhang, Haoran Jiang, Shan Xuan, Shichang

【Source】COMPUTER COMMUNICATIONS CCF-C

【影响因子】5.047

【主题类别】

区块链技术-协同技术-联邦学习

【Abstract】Decentralized federated learning integrates advanced technologies, including distributed computing and secure encryption methodologies, to facilitate a robust and efficient mechanism for safeguarding data privacy and security during collaborative model training endeavors. The incorporation of blockchain technology into Federated Learning provides a transformative framework characterized by its inherent decentralization and data immutability, making it a focal point of contemporary research inquiry. The literature on the integration of blockchain technology with federated learning frameworks is presently deficient in comprehensive summary works. Such summaries are essential for advancing understanding of the implementation challenges and for guiding future research efforts in this domain. Therefore, in this work, we first summarize a typical decentralized federated learning framework based on blockchain and describe its operational workflow and its applications in the fields of the Internet of Things, the Internet of Vehicles, etc. A systematic summary of the challenges confronting this framework and an analysis of the solutions proposed to address these challenges are provided. Finally, this work provides insight into the possible future research directions.

你可以尝试使用大模型来生成摘要 立即生成

【Keywords】Blockchain; Federated learning; Decentralized federated learning; Data security

【发表时间】2024

【收录时间】2024-03-06

【文献类型】 综述

【DOI】 10.1016/j.comcom.2023.12.042

【Author】 Alsharif, Mohammed H. Jahid, Abu Kannadasan, Raju Kim, Mun-Kyeom

【Source】ENERGY REPORTS

【影响因子】4.937

【主题类别】

区块链应用-实体经济-电力领域

【Abstract】As the world continues to seek sustainable and efficient energy solutions, the integration of advanced technologies into smart energy grid management (SEGM) becomes a paramount focus. The advent of Sixth Generation (6G) wireless networks promises to revolutionize the way energy grids are monitored, controlled, and optimized. This review paper explores the potential of 6G wireless networks in the context of SEGM. It discusses the vision and potential techniques that can be harnessed to unlock the full capabilities of 6G networks. The paper delves into the challenges and opportunities presented by 6G technology, addressing issues such as scalability, security, real-time monitoring, and dynamic spectrum access. Moreover, it explores how 6G wireless networks can enable seamless integration with other advanced technologies, such as blockchain and cybertwin, to enhance the resilience and reliability of smart energy grids. The comprehensive review aims to shed light on the transformative role of 6G wireless networks, paving the way for a sustainable and intelligent future in energy grid management.

你可以尝试使用大模型来生成摘要 立即生成

【Keywords】6G wireless networks; 6G vision; 6G applications; Smart energy grid; Next-generation smart grid; Sustainable smart grid evolution; AI in energy grids; Smart grid data communication; Intelligent management grid; Smart grid reliability

【发表时间】2024

【收录时间】2024-03-06

【文献类型】 综述

【DOI】 10.1016/j.egyr.2024.01.011

【Author】 Wang, Xinchao Wang, Wei Huang, Cheng Cao, Ping Zhu, Youwen Wu, Qihui

【Source】IEEE SYSTEMS JOURNAL

【影响因子】4.802

【主题类别】

区块链技术-协同技术-物联网

【Abstract】Identity authentication is an essential element for industrial Internet of Things (IIoT), which guarantees secure access control for various devices. Existing authentication schemes face some security threats, including temporary secret leakage attack, key recovery attack, and forgery attack. In this article, we introduce a blockchain-based certificateless conditional anonymous authentication (BCCA) scheme specifically designed for IIoT. To optimize the authentication efficiency, BCCA employs elliptic curve design to avoid the relatively time-consuming bilinear pairing operation. Additionally, we introduce a precomputation strategy, allowing users to prepare essential materials in advance, and one-time verification support for batch signatures is applied, thus reducing authentication latency. To further enhance the security, random verification checksums are employed to counter key recovery attack, and a combination of long-term and short-term secrets is used to mitigate temporary secret leakage attack. Simulation results demonstrate that our scheme has advantages in both security and computational cost.

你可以尝试使用大模型来生成摘要 立即生成

【Keywords】Authentication; blockchain; certificateless; industrial Internet of Things (IIoT); security

【发表时间】2024

【收录时间】2024-03-06

【文献类型】 实验仿真

【DOI】 10.1109/JSYST.2023.3345370

【Author】 Huang, Hexiang Zhang, Xuan Wang, Jishu Gao, Chen Li, Xue Zhu, Rui Ma, Qiuying

【Source】IEEE TRANSACTIONS ON COMPUTATIONAL SOCIAL SYSTEMS

【影响因子】4.747

【主题类别】

区块链治理-技术治理-诈骗检测

【Abstract】Recent years, the successful application of blockchain in cryptocurrency has attracted a lot of attention, but it has also led to a rapid growth of illegal and criminal activities. Phishing scams have become the most serious type of crime in Ethereum. Some existing methods for phishing scams detection have limitations, such as high complexity, poor scalability, and high latency. In this article, we propose a novel framework named phishing detection on Ethereum via augmentation ego-graph based on graph neural network (PEAE-GNN). First, we obtain account labels and transaction records from authoritative websites and extract ego-graphs centered on labeled accounts. Then we propose a feature augmentation strategy based on structure features, transaction features and interaction intensity to augment the node features, so that these features of each ego-graph can be learned. Finally, we present a new graph-level representation, sorting the updated node features in descending order and then taking the mean value of the top n to obtain the graph representation, which can retain key information and reduce the introduction of noise. Extensive experimental results show that PEAE-GNN achieves the best performance on phishing detection tasks. At the same time, our framework has the advantages of lower complexity, better scalability, and higher efficiency, which detects phishing accounts at early stage.

你可以尝试使用大模型来生成摘要 立即生成

【Keywords】Phishing; Feature extraction; Task analysis; Blockchains; Graph neural networks; Scalability; Topology; Blockchain; Ethereum; graph classification; graph neural network; phishing detection

【发表时间】2024

【收录时间】2024-03-06

【文献类型】 实验仿真

【DOI】 10.1109/TCSS.2023.3349071

【Author】 Ha, Le Thanh

【Source】CLEAN TECHNOLOGIES AND ENVIRONMENTAL POLICY

【影响因子】4.700

【主题类别】

区块链治理-市场治理-数字货币

【Abstract】Climate change is causing issues in all areas of the economy, and robotic and artificial intelligence development have the potential to prevent these risks. We investigate quantile spillovers using quantile vector autoregression (QVAR), robotics, artificial intelligence development, and carbon risk. Using global data on a global daily dataset from carbon emission future (CEF), Global X Robotics & artificial intelligence (BOTZ), iShares Robotics and Artificial Intelligence Multisector (IRBO), First Trust Nasdaq Artificial Intelligence and Robotics (ROBT) from April 1, 2019, to October 28, 2022, our study illustrates that there exists considerable dynamic connectedness between robotic, artificial intelligence development, and carbon risk. The COVID-19 epidemic and the Russia-Ukraine war caused a brief change in direct connectivity over quantiles. CEF consistently receives shocks from the system, while IRBO and ROBT transmit significant shocks to systems. The dynamic net pairwise directional connectivity in the context of quantiles demonstrates that the common eigen factor (CEF) mainly absorbs the influences of the three other variables, especially during COVID-19. This dynamic net pairwise directional connectivity across quantiles demonstrates how unknown events, such as the Ukraine-Russia conflict and the COVID-19 epidemic, affect investor mood as well as both environmentally unfriendly and environmentally beneficial cryptocurrencies. Hence, our paper calls for policy designs that maximize the positive effects of robotic and AI development on the carbon emission market.

你可以尝试使用大模型来生成摘要 立即生成

【Keywords】QVAR; Network interlinkages; Artificial intelligence; Fintech innovation; Carbon risk; COVID-19; Ukraine-Russia conflict; F3; G12; Q43

【发表时间】2024

【收录时间】2024-03-06

【文献类型】 实证数据

【DOI】 10.1007/s10098-024-02744-y

【Author】 Javadpour, Amir Sangaiah, Arun Kumar Zhang, Weizhe Vidyarthi, Ankit Ahmadi, Hamidreza

【Source】JOURNAL OF GRID COMPUTING CCF-C

【影响因子】4.674

【主题类别】

区块链应用-实体经济-工业互联网

【Abstract】This study presents an environmentally friendly mechanism for task distribution designed explicitly for blockchain Proof of Authority (POA) consensus. This approach facilitates the selection of virtual machines for tasks such as data processing, transaction verification, and adding new blocks to the blockchain. Given the current lack of effective methods for integrating POA blockchain into the Cloud Industrial Internet of Things (CIIoT) due to their inefficiency and low throughput, we propose a novel algorithm that employs the Dynamic Voltage and Frequency Scaling (DVFS) technique, replacing the periodic transaction authentication process among validator candidates. Managing computer power consumption becomes a critical concern, especially within the Internet of Things ecosystem, where device power is constrained, and transaction scalability is crucial. Virtual machines must validate transactions (tasks) within specific time frames and deadlines. The DVFS technique efficiently reduces power consumption by intelligently scheduling and allocating tasks to virtual machines. Furthermore, we leverage artificial intelligence and neural networks to match tasks with suitable virtual machines. The simulation results demonstrate that our proposed approach harnesses migration and DVFS strategies to optimize virtual machine utilization, resulting in decreased energy and power consumption compared to non-DVFS methods. This achievement marks a significant stride towards seamlessly integrating blockchain and IoT, establishing an ecologically sustainable network. Our approach boasts additional benefits, including decentralization, enhanced data quality, and heightened security. We analyze simulation runtime and energy consumption in a comprehensive evaluation against existing techniques such as WPEG, IRMBBC, and BEMEC. The findings underscore the efficiency of our technique (LBDVFSb) across both criteria.

你可以尝试使用大模型来生成摘要 立即生成

【Keywords】Blockchain; Improving resources; Internet of Things; Decentralized; DVFS; Industrial Internet of Things

【发表时间】2024

【收录时间】2024-03-06

【文献类型】 实验仿真

【DOI】 10.1007/s10723-024-09751-9

【Author】 Li, Huijie Gao, Jinwu Li, Xiang

【Source】OCEAN & COASTAL MANAGEMENT

【影响因子】4.295

【主题类别】

区块链应用-实体经济-航运领域

【Abstract】Blockchain technology has already been explored and used in many industries, while the shutdown of shipping blockchain platform TradeLens poses a substantial challenge to the blockchain adoption in the shipping supply chain. Motivated by this practical issue, we develop a Hotelling model to study two competitive shipping platforms' pricing strategies and blockchain technology investment preferences in three scenarios including both shipping platforms invest nothing, only one shipping platform invests, as well as both shipping platforms invest. The liner companies and forwarders in the two-sided markets may join only one shipping platform (i.e., singlehoming) or join two shipping platforms simultaneously (i.e., multihoming). Our results suggest that whether the blockchain technology is introduced or not, the shipping platforms in each scenario provide the pricing strategies via subsidizing and charging the entry fees for the liner companies and forwarders when singlehoming occurs, whereas the only pricing strategy is to demand the entry fees when multihoming occurs. Moreover, we find that the shipping platforms' investment preferences over blockchain technology would not be affected by the liner companies' and forwarders' singlehoming or multihoming behavior. The shipping platform without blockchain technology investment can achieve profit improvement by free riding via the other shipping platform's blockchain investment decision given certain investment cost, while the shipping platform with blockchain technology investment instead suffers a loss of profitability due to its investment decision. In particular, compared to singlehoming, the shipping platforms may obtain higher equilibrium profits when multihoming occurs among three scenarios.

你可以尝试使用大模型来生成摘要 立即生成

【Keywords】Two-sided shipping markets; Blockchain technology; Platform competition; Multihoming

【发表时间】2024

【收录时间】2024-03-06

【文献类型】 实证数据

【DOI】 10.1016/j.ocecoaman.2023.106932

【Author】 Conlon, Thomas Corbet, Shaen Hou, Yang (Greg)

【Source】JOURNAL OF INTERNATIONAL FINANCIAL MARKETS INSTITUTIONS & MONEY

【影响因子】4.217

【主题类别】

区块链治理-市场治理-市场分析

【Abstract】This paper investigates the price discovery relationships between FTT Token, issued by the cryptocurrency exchange FTX, and a set of assets and liabilities held by FTX amid a period of catastrophic financial decline by applying novel information flow measurement techniques. Results indicate that during key phases associated with the collapse of FTX, FTT Token had an informational lead over multiple assets, including cryptocurrencies such as Ethereum. Furthermore, we identify significant interactions between the FTT Token and both Robinhood shares and the token Serum, raising concerns about the direct influence of permissionless, technically valueless tokens on other assets and the potential challenges to market stability and investor protection. Our findings underscore the need for stronger policy -making, regulatory, and ethical considerations in cryptocurrency markets.

你可以尝试使用大模型来生成摘要 立即生成

【Keywords】Cryptocurrency; Tokens; Corporate failure; Information flow; Price discovery

【发表时间】2024

【收录时间】2024-03-06

【文献类型】 实证数据

【DOI】 10.1016/j.intfin.2024.101940

【Author】 Malisic, Bojana Misic, Nemanja Krco, Srdjan Martinovic, Aleksandra Tinaj, Sandra Popovic, Tomo

【Source】SUSTAINABILITY

【影响因子】3.889

【主题类别】

区块链应用-实体经济-食品供应链

【Abstract】Blockchain offers decentralized, trustworthy and immutable data storage based on distributed ledger technology. Blockchain technology is recognized as an innovation enabler in many areas, with the food supply chain being one of them. This paper provides a systematic literature review of the current state of adoption of blockchain technology in the agri-food sector, specifically with a focus on the wine supply chain. Blockchain has the potential to improve the traceability and authenticity of the data provenance of wine products, increase consumer trust, and reduce fraud and errors. With these goals in mind, this study identifies the main research questions pertinent to the value proposition and competitive advantage of blockchain technology in the wine value chain and key players involved in the authentication and value chain recording. The PRISMA methodology was adopted to identify, screen and select only the relevant studies that were included in the analysis. This study also addresses the limitations and challenges for adoption, such as high implementation cost and lack of competences, and the need for standardized protocols and regulations. Finally, this systematic literature review includes an analysis of reports of blockchain applications in the wine sector and outlines the recommendations for future research to further explore the potential of blockchain-based solutions that could benefit all stakeholders across the wine value chain.

你可以尝试使用大模型来生成摘要 立即生成

【Keywords】blockchain; data provenance; food sustainability; systematic literature review; traceability; wine supply chain

【发表时间】2023

【收录时间】2024-03-06

【文献类型】 综述

【DOI】 10.3390/su151914408

【Author】 Maythu, Yin Kwok, Andrei O. J. Teh, Pei-Lee

【Source】HELIYON

【影响因子】3.776

【主题类别】

区块链应用-实体经济-旅游领域

【Abstract】The use cases of blockchain as an innovative technology have increasingly captured the attention of tourism enterprises. To date, the literature tends to discuss blockchain's advantages rather than how early enterprise adopters and innovators experience and perceive the technology. As such, the extent of technology diffusion is not well understood. This study critically explores the factors influencing blockchain diffusion in tourism and how blockchain innovation is diffused in tourism. We conducted semistructured interviews with founders and senior executives of tourism enterprises in the United States and Europe who are early adopters and innovators of blockchain in tourism. From the thematic analysis, our empirical findings indicate that blockchain has much to offer despite the nascent link between blockchain's business value to an enterprise's strategic plans and the limited success of use cases in tourism. We summarize the findings in a conceptual framework and offer propositions based on the antecedents (motivators and drivers and challenges and barriers) of blockchain diffusion of innovation for enterprises to achieve competitive advantage. The propositions provide a research agenda to guide the strategic implementation of blockchain.

你可以尝试使用大模型来生成摘要 立即生成

【Keywords】Competitive advantage; Diffusion of innovation; Blockchain; Research agenda; Motivators and drivers; Challenges and barriers

【发表时间】2024

【收录时间】2024-03-06

【文献类型】 实证数据

【DOI】 10.1016/j.heliyon.2024.e24675

【Author】 Xu, Jie Ming, Yulong Wu, Zihan Wang, Cong Jia, Xiaohua

【Source】IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS CCF-A

【影响因子】3.757

【主题类别】

区块链技术-核心技术-分片区块链

【Abstract】Recent advances in cryptocurrencies have sparked significant interest in blockchain technology. However, scalability issues remain a major challenge for wide adoption of blockchains. Sharding is a promising approach to scale blockchains, but existing sharding-based blockchains fail to achieve expected performance gains due to limitations in cross-shard transaction processing. In this paper, we propose X-shard, a blockchain system that optimizes cross-shard transaction processing, achieving high effective throughput and low processing latency. First, we allocate transactions to shards based on historical transaction patterns to minimize cross-shard transactions. Second, we take an optimistic strategy to process cross-shard transactions in parallel as sub-transactions within input shards, thereby accelerating transaction processing. Finally, we employ a cross-shard commit protocol with threshold signatures to reduce communication overhead. We implement and deploy X-shard on Amazon EC2 clusters. Experimental results validate our theoretical analysis and show that as the number of shards increases, X-shard achieves nearly linear scaling in effective throughput and decreases in transaction processing latency.

你可以尝试使用大模型来生成摘要 立即生成

【Keywords】Blockchain scalability; distributed system; optimistic concurrency control; sharding

【发表时间】2024

【收录时间】2024-03-06

【文献类型】 实验仿真

【DOI】 10.1109/TPDS.2024.3361180

【Author】 Liu, Guijiang Xie, Haibo Wang, Wenming Huang, Haiping

【Source】JOURNAL OF CLOUD COMPUTING-ADVANCES SYSTEMS AND APPLICATIONS

【影响因子】3.418

【主题类别】

区块链应用-实体经济-医疗领域

【Abstract】With the rapid development of the Internet of Medical Things (IoMT) and the increasing concern for personal health, sharing Electronic Medical Record (EMR) data is widely recognized as a crucial method for enhancing the quality of care and reducing healthcare expenses. EMRs are often shared to ensure accurate diagnosis, predict prognosis, and provide health advice. However, the process of sharing EMRs always raises significant concerns about potential security issues and breaches of privacy. Previous research has demonstrated that centralized cloud-based EMR systems are at high risk, e.g., single points of failure, denial of service (DoS) attacks, and insider attacks. With this motivation, we propose an EMR sharing scheme based on a consortium blockchain that is designed to prioritize both security and privacy. The interplanetary file system (IPFS) is used to store the encrypted EMR while the returned hash addresses are recorded on the blockchain. Then, the user can authorize other users to decrypt the EMR ciphertext via the proxy re-encryption algorithm, ensuring that only authorized personnel may access the files. Moreover, the scheme attains personalized access control and guarantees privacy protection by employing attribute-based access control. The safety analysis shows that the designed scheme meets the expected design goals. Security analysis and performance evaluation show that the scheme outperforms the comparison schemes in terms of computation and communication costs.

你可以尝试使用大模型来生成摘要 立即生成

【Keywords】Blockchain; Proxy re-encryption; EMR sharing; IPFS; Data security

【发表时间】2024

【收录时间】2024-03-06

【文献类型】 实验仿真

【DOI】 10.1186/s13677-024-00608-w

【Author】 Kumar, Prabhat Javeed, Danish Kumar, Randhir Islam, A. K. M. Najmul

【Source】SOFTWARE-PRACTICE & EXPERIENCE

【影响因子】3.200

【主题类别】

区块链技术-协同技术-人工智能

【Abstract】Artificial Intelligence (AI) based cyber threat detection tools are widely used to process and analyze a large amount of data for improved intrusion detection performance. However, these models are often considered as black box by the cybersecurity experts due to their inability to comprehend or interpret the reasoning behind the decisions. Moreover, AI-based threat hunting is data-driven and is usually modeled using the data provided by multiple cloud vendors. This is another critical challenge, as a malicious cloud can provide false information (i.e., insider attacks) and can degrade the threat-hunting capability. In this paper, we present a blockchain-enabled eXplainable AI (XAI) for enhancing the decision-making capability of cyber threat detection in the context of Smart Healthcare Systems. Specifically, first, we use blockchain to validate and store data between multiple cloud vendors by implementing a Clique Proof-of-Authority (C-PoA) consensus. Second, a novel deep learning-based threat-hunting model is built by combining Parallel Stacked Long Short Term Memory (PSLSTM) networks with a multi-head attention mechanism for improved attack detection. The extensive experiment confirms its potential to be used as an enhanced decision support system by cybersecurity analysts.

你可以尝试使用大模型来生成摘要 立即生成

【Keywords】blockchain; cybersecurity; explainable AI; intrusion detection system; smart healthcare system

【发表时间】2024

【收录时间】2024-03-06

【文献类型】 实验仿真

【DOI】 10.1002/spe.3319

【Author】 Wan, Changxu Wang, Ying Xu, Jianbo Wu, Junjie Zhang, Tiantian Wang, Yulong

【Source】ELECTRONICS

【影响因子】2.690

【主题类别】

区块链技术-协同技术-联邦学习

【Abstract】Traditional federated learning addresses the data security issues arising from the need to centralize client datasets on a central server for model training. However, this approach still poses privacy protection risks. For instance, central servers cannot verify privacy leaks resulting from poisoning attacks by malicious clients. Additionally, adversarial sample attacks can infer specific samples from the original data by testing the local models on client devices. This paper proposes a federated learning privacy protection method combining distillation defense technology with blockchain architecture. The method utilizes distillation defense technology to reduce the sensitivity of client devices participating in federated learning to perturbations and enhance their ability to resist adversarial sample attacks locally. This not only reduces communication overhead and improves learning efficiency but also enhances the model's generalization ability. Furthermore, the method leverages the "decentralized" nature of blockchain architecture as a trusted record-keeping mechanism to audit information interactions among clients and shared model parameters. This addresses privacy leakage issues resulting from poisoning attacks by some clients during the model construction process. Simulation experiment results demonstrate that the proposed method, compared with traditional federated learning, ensures model convergence, detects malicious clients, and improves the participation level of highly reputable clients. Moreover, by reducing the sensitivity of local clients to perturbations, it enhances their ability to effectively resist adversarial sample attacks.

你可以尝试使用大模型来生成摘要 立即生成

【Keywords】decentralization; distillation defense; blockchain; privacy protection; federated learning

【发表时间】2024

【收录时间】2024-03-06

【文献类型】 实验仿真

【DOI】 10.3390/electronics13040679

【Author】 Karthi, V. Revathi, S. Kumaraswamy, Ramesh Anthonisamy, Arun Vijayakumar, S. D. Ramkumar, A.

【Source】ELECTRIC POWER COMPONENTS AND SYSTEMS

【影响因子】1.276

【主题类别】

区块链应用-实体经济-电力领域

【Abstract】The growing prominence of solar energy in decentralized renewable energy landscapes underscores the need for efficient solar energy trading mechanisms and seamless grid integration. This decentralized renewable energy sources, especially solar energy, present a significant prospect for the production of sustainable energy. This investigation explores the use of blockchain technology as a basic framework to tackle the problems associated with grid integration and solar energy trading in a decentralized setting. It uses the built-in advantages of blockchain technology, such as trust, transparency, and smart contract automation, to address the design and execution of a platform tailored for solar energy. As a result, the system efficiency increased to 93% and the transaction confirmation time was cut from 4.5 to 2.5 s with the lowest possible transaction cost. Furthermore, this study intends to offer insightful information about the technological viability, security, and scalability of blockchain solutions in the field of solar energy, while highlighting the significance of indicators of performance for an in-depth evaluation. This novel strategy is a crucial development for the field of green energy as it promises to revolutionize the way solar energy is traded, used, and integrated into modern grids.

你可以尝试使用大模型来生成摘要 立即生成

【Keywords】blockchain; solar energy trading; grid integration; smart contracts; decentralized renewable energy; distributed ledger technology; sustainability; peer-to-peer

【发表时间】2024

【收录时间】2024-03-06

【文献类型】 实验仿真

【DOI】 10.1080/15325008.2024.2316250