【Author】 Cai, Lingyi Hu, Qiwei Jiang, Tao Niyato, Dusit
【影响因子】12.777
【主题类别】
区块链应用-虚拟经济-数字孪生
区块链技术-协同技术-联邦学习
【Abstract】With the development of digital twin (DT) technology, the DT network (DTN) has emerged to represent virtually the physical network by building physical entities as interactive DT models. However, the DTN faces the challenge of privacy leakage due to the collection of private data in the DT model building process. Additionally, massive data uploaded to the DTN for centralized processing leads to security issues of single-point failure and poisoning attacks. In this article, we propose blockchain- enabled secure federated learning (FL) for constructing a decentralized and privacy-preserving DTN. Specifically, we utilize the FL paradigm and homomorphic encryption method to locally build DT models at the ciphertext level. Then, we propose integrating blockchain into FL to construct a decentralized architecture for the DTN to avoid single-point failure. Moreover, we devise the proof-of-gradient consensus mechanism to facilitate trusted interactions among DT models to resist poisoning attacks. Finally, the security analysis and performance evaluations demonstrate the superiority of the proposed schemes.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】Data models; Servers; Computational modeling; Blockchains; Digital twins; Cryptography; Training; Adaptation models; Buildings; Federated learning
【发表时间】2024
【收录时间】2024-10-28
【文献类型】 理论模型
【DOI】 10.1109/MWC.007.2400141
CCF-B
【影响因子】9.551
【主题类别】
区块链应用-实体经济-电力领域
【Abstract】Multi-domain vehicle to grid (V2G) is a network environment in which numerous service providers offer charging and discharging services to EV users. This can enhance energy management and traffic flow for efficient intelligent transportation systems (ITS). However, the combination of multiple domains can suffer from various security vulnerabilities, highlighting the need for robust countermeasures. Moreover, existing multi-domain V2G protocols utilized a central trusted authority (TA) which can create a single point of failure (SPOF), or required high computational resources. In this paper, we propose a multi-domain authentication protocol for secure and efficient V2G services using consortium blockchain. The proposed protocol provides lightweight intra-domain authentication using hash functions and XOR operators. Furthermore, the proposed protocol ensures secure cross-domain authentication by integrating elliptic curve cryptography (ECC) and physical unclonable function (PUF). Therefore, the proposed protocol can establish trust, enable efficient communications, and prevent congestion at charging stations. To validate security robustness, comprehensive evaluations are conducted using "Real-Or-Random (ROR) model"", Scyther tool", and informal analyses. Comparative computational overheads of the proposed and related protocols are measured using "Multiprecision Integer and Rational Arithmetic Cryptographic Library (MIRACL)" testbed experiments. Additionally, a simulation of the practical deployment is conducted using "Network Simulator-3 (NS-3)". Results indicate that the proposed protocol can improve ITS by providing secure and efficient services for multi-domain V2G environments.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】Protocols; Security; Authentication; Physical unclonable function; Robustness; Charging stations; Computational modeling; Blockchains; Threat modeling; Electric vehicle; multi-domain; mutual authentication; security; vehicle to grid; vehicle to grid
【发表时间】2024
【收录时间】2024-10-28
【文献类型】 实验仿真
【影响因子】8.702
【主题类别】
区块链应用-实体经济-供应链
区块链技术-协同技术-数字孪生
【Abstract】We tackle the problem of digitalization of supply chains, focusing on the collaboration and sharing of information. By generalizing the notion of digital twins, we review, develop, and conceptualize the (emerging) notion of digital twins of supply chains (DTofSC). While digital twins is an active research area with data available from numerous industry projects, its application to supply chains is just emerging as a cross discipline stemming from decades of maturing the notion of digital supply chains. While digital twins has been used in supply chains, the notion of digitalization of supply chains is only a nascent area, with imprecise definitions beyond key metaphors (e.g., visibility, traceability); as we conceptualize, the overall vision is to create technical and organizational mechanisms enabling any supply chain to be monitored and controlled from, e.g., a dashboard screen. After a literature review on the intersections between digital supply chains, digital twins, and digital technologies (e.g., blockchain), we propose a synthesis systems architecture of DTofSC, identify a key requirement gap (that we term addressability), and ground our contributions, and in the absence of real-world use-cases in practice, we apply our conceptualized systems architecture to battery recycling based on feedback from an industry-targeted workshop.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】Supply chains; Digital twins; Batteries; Recycling; Reviews; Systems architecture; Real-time systems; Blockchains; digital supply chains; digital twins (DT); digital twins of supply chains (DTofSC); supply chains (SCs)
【发表时间】2024
【收录时间】2024-10-28
【文献类型】 综述
【DOI】 10.1109/TEM.2024.3468177
【Author】 Liu, Yakun Chen, Yan
【影响因子】8.235
【主题类别】
区块链治理-市场治理-系统风险
【Abstract】This paper investigates whether investors can achieve higher returns by holding cryptocurrencies with lower asymmetry risk. First, using a non-parametric bootstrap resampling method, we found that cryptocurrencies with larger market capitalizations exhibit more left-skewed performance, while those with smaller market capitalizations display more right-skewed performance. This finding is consistent with the results of Jiang et al. (2020) in the stock market. Second, both portfolio-level analyses and cross-sectional regressions at the cryptocurrency level reveal a negative cross-sectional relationship between asymmetry risk and future returns in the cryptocurrency market. Additionally, our findings indicate that skewness in the cryptocurrency market is driven by idiosyncratic risk rather than systematic risk. This contrasts with Langlois (2020), who found that systematic skewness risk outweighs idiosyncratic risk in the stock market. Finally, in addition to the risk-return tradeoff theory, the limits-to-arbitrage theory also provides explanatory insight into these results. Collectively, our findings underscore the significant role of asymmetry risk in determining cryptocurrency prices.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】Cryptocurrency; Asymmetry risk; Return predictability
【发表时间】2024
【收录时间】2024-10-28
【文献类型】 实证数据
CCF-A
【影响因子】7.231
【主题类别】
区块链治理-技术治理-诈骗检测
【Abstract】With the popularity of Non-Fungible Tokens (NFTs), the high value of NFTs makes them a target for phishing scammers, which harms the security and reliability of the Web3 NFT ecosystem. Despite the significance of this issue, there is a lack of systematic research in the area of emerging NFT phishing scams. To address this gap, we are the first to conduct a case retrospective analysis and empirical measurement study of real-world historical NFT phishing scams on Ethereum. We collect and publicly release the first NFT phishing dataset which includes 1,625 NFT phishing accounts and transaction records as of August 2023. We further categorize the existing scams into four phishing patterns and investigate their distinguishable behaviors. Then, we reveal the modus operandi preferences and economic impacts to characterize NFT phishing scams. We find that NFT phishers stole 67,188 NFTs, with a total direct selling profit of ${\$}$ 20.92 million. We also observe that scammers favor certain categories and collections of NFTs, coupled with signs of gang theft. Furthermore, we design a variety of account features for the classification task of NFT phishers based on empirical conclusions. Experimental results on real-world NFT transaction data demonstrate the effectiveness of these features in detecting NFT phishing accounts, and outperform traditional phishing detection methods with 41% average Precision and 44% average Recall.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】Nonfungible tokens; Phishing; Smart contracts; Cryptocurrency; Open source software; Feature extraction; Security; Web3; non-fungible tokens; ethereum; phishing scams; security
【发表时间】2024
【收录时间】2024-10-28
【文献类型】 实证数据
【影响因子】4.996
【主题类别】
区块链应用-实体经济-环保领域
【Abstract】Widespread use of lead acid batteries (LABs) is resulting in the generation of million tons of battery waste, globally. LAB waste contains critical and hazardous materials, which have detrimental effects on the environment and human health. In recent times, recycling of the LABs has become efficient but the collection of batteries in developing countries is not efficient, which led to the non-professional treatment and recycling of these batteries in the informal sector. This paper proposes a blockchain-enabled architecture for LAB circularity, which ensures authentic, traceable and transparent system for collection and treatment of batteries. The stakeholders-battery manufacturers, distributors, retailers, users, and validators (governments, domain experts, third party experts, etc.)-are integrated in the circular loop through a blockchain network. A mobile application user interface is provided to all the stakeholders for the ease of adoption. The batteries manufactured and supplied in a geographical region as well as the recycled materials at the battery end-of-life are traced authentically. This architecture is expected to be useful for the battery manufacturers to improve their extended producer responsibility and support responsible consumption and production.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】Lead acid battery; Material circularity; Blockchain; Supply chain; Traceability; Hazardous and critical materials
【发表时间】2024
【收录时间】2024-10-28
【文献类型】 理论模型
【影响因子】3.778
【主题类别】
区块链治理-市场治理-市场分析
区块链治理-市场治理-数字货币
【Abstract】The Ethereum blockchain and its ERC20 token standard have revolutionized the landscape of digital assets and decentralized applications. ERC20 tokens are programmable and interoperable tokens, enabling various applications and token economies. Transaction graphs, representing the flow of the value between wallets within the Ethereum network, have played a crucial role in understanding the system's dynamics, such as token transfers and the behavior of traders. Here, we explore the evolution of daily transaction graphs of ERC20 token transactions, which sheds light on the trader's behavior during the Black Swan Events - 2018 crypto crash and the COVID-19 pandemic. By using the tools from network science and differential geometry, we analyze 0.98 billion of ERC20 token transaction data from November 2015 to January 2023. Our analysis reveals an increase in diverse interaction among the traders and a greater adoption of ERC20 tokens in a maturing Ethereum ERC20 financial ecosystem after the Crypto Crash 2018 and the COVID-19 pandemic. Before the crash and the COVID-19 pandemic, most traders interacted with other traders in an isolated or restricted manner, with each trader focusing solely on either buying or selling activities. However, after the crash and during the pandemic, most traders diversely interacted among themselves by participating in both buying and selling activities. In addition, we observe no significant negative impact of the COVID-19 pandemic on user behavior in the financial ecosystem.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】Ethereum blockchain; Financial networks; Transaction graph; Forman-Ricci curvature
【发表时间】2024
【收录时间】2024-10-28
【文献类型】 观点阐述
【影响因子】3.778
【主题类别】
区块链治理-市场治理-市场分析
区块链治理-市场治理-数字货币
【Abstract】In recent years, Bitcoin has garnered attention as a digital currency, prompting increasing debate regarding its effects on traditional financial markets, particularly the US dollar. This study investigates the relationship between Bitcoin and the US dollar, especially in the contexts of speculative attacks, where investors attempt to devalue a currency, and short squeezes, where rapid price rises force short sellers to quickly buy back assets to avoid further losses. The study employs a novel hybrid model combining an autoregressive moving average, Generalized Autoregressive Conditional Heteroskedasticity, and Wavelet Neural Networks techniques with neural networks approaches. The results suggest that significant trading activity in Bitcoin/US dollar, particularly during speculative attacks and short squeezes, can substantially impact the US dollar/EUR market, increasing price volatility as traders adjust their strategies. These adjustments, along with risk management strategies, drive higher trading volumes and further volatility. Our findings demonstrate that our novel hybrid model combined with Quantum Recurrent Neural Networks provides the most accurate predictions, offering valuable insights to inform trading strategies in both Bitcoin/US dollar and US dollar/EUR markets. This study has important implications for policymakers and market participants, emphasising the need to understand the relationship between Bitcoin and the US dollar for financial stability and effective policy formulation. It also highlights the necessity of advanced modeling techniques to accurately predict cryptocurrency market behavior.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】Cryptocurrency markets; Bitcoin; Volatility; ARIMA-EGARCH; Speculative attack; Short squeeze; Neural Networks; Wavelet analysis
【发表时间】2024
【收录时间】2024-10-28
【文献类型】 案例研究
【Author】 Suhaimi, Nur Hanis Sabrina Kamarudin, Nazhatul Hafizah Khalid, Mohd Nor Akmal Tahir, Ibrahim Mohamed, Muhammad Amir Afiq
【影响因子】3.476
【主题类别】
区块链应用-实体经济-通信领域
【Abstract】Satellite communication (SatCom) is essential in modern telecommunication infrastructure, providing global connectivity and overcoming limitations of the terrestrial network. With the emergence of vertical heterogeneous networks integrating terrestrial and non-terrestrial networks, authentication becomes crucial to address security challenges, especially in low Earth orbit SatCom. This review comprehensively explores the authentication mechanisms, challenges, and future research directions to offer a holistic view of authentication in satellite communication networks. This study adopts a systematic approach that follows five phases: research planning, search execution, study selection, data classification, and study mapping. Explores recent research on various authentication schemes in SatCom, focusing on fundamental research questions to uncover the complexities associated with authentication in this domain. Existing authentication protocols are analyzed by using a multi-criteria classification approach to highlight their strengths, weaknesses, and security implications. By investigating current authentication systems in SatCom and identifying emerging trends, this review offers a roadmap for future research, providing valuable insights for practitioners, policymakers, and researchers. Enhances understanding of SatCom authentication complexity, laying the groundwork for resilient security measures crucial to the sustainable advancement of Space-Ground network technology.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】Authentication; Security; Systematics; Cryptography; Protocols; Market research; Databases; Satellite communications; Satellite security system; SatCom authentication; space-ground security; physical layer authentication; space technology; satellite attacks
【发表时间】2024
【收录时间】2024-10-28
【文献类型】 综述
【Author】 Pati, Abhilash Panigrahi, Amrutanshu Parhi, Manoranjan Kumar Pattanayak, Binod Sahu, Bibhuprasad Kant, Shashi
【影响因子】3.476
【主题类别】
区块链技术-协同技术-雾计算
【Abstract】Technology has a significant impact on medical applications at the current moment. Contemporary computers are capable of processing a lot of patient medical records quickly. Due to recent advancements in the Internet-of-Things (IoT) and medical applications, patient data may be dispersed over several places. Worldwide, the IoT connects numerous devices for e-healthcare systems. The medical data monitoring and tracking field, exercise programs, and remote medical help are expanding within the e-healthcare systems. IoT-based technologies are now being used in e-healthcare systems, which can relieve pressure on e-healthcare systems, lower medical expenses, and speed up computing and processing. In the IoT setting, cloud computing, which contains centralized data centers, was developed to manage more extensive and sophisticated e-healthcare data. The central server governs the data for all IoT devices. Problems with IoT and Cloud integration only include latency, bandwidth overuse, delays in real-time responses, security, privacy, integrity, etc. The ideas of fog computing and edge computing were developed to solve the above-mentioned problems. A thorough literature overview on Fog-based medical applications using IoT is provided in this article, i.e., Fog of Medical Things (FoMT), that explores the simulators that may be employed to create and assess new Fog-related theories as well as the key attributes of Fog computing frameworks. This review also emphasizes the difficulties in the field and some unanswered questions. This study can serve as a crucial road map for the future creation of Fog-based e-healthcare IoT applications.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】FoMT; IoT; fog computing; cloud computing; simulation tools; e-healthcare systems; FoMT; IoT; fog computing; cloud computing; simulation tools; e-healthcare systems
【发表时间】2024
【收录时间】2024-10-28
【文献类型】 理论模型
【影响因子】3.476
【主题类别】
区块链应用-实体经济-投票领域
【Abstract】Electronic voting systems have often associated with issues of security, transparency, and limited accessibility, particularly for people with disability, elderly, and visually impaired voters. These systems, impeded by complex authentication procedures and non-intuitive user interfaces, have also struggled to ensure voter trust and widespread participation. To address these issues, this paper presents a new electronic voting system that combines the gesture recognition with blockchain technology. The proposed system has two phases, the first one is a user identification phase using a pre-trained dataset based on both cvzone and Dlib tools for face and finger identifications. Gestures from the face and hands, such as eyebrow and nose movements are used as authentication mechanisms as well as a mean of input into the system. The second is a voting process phase which uses the blockchain technology. This new approach strengthens the security and transparency of voting through a tamper-proof ledger provided by the blockchain technology, as well as enhances considerably the inclusiveness and also user friendliness. Real time simulations show that the user interaction times for different age groups ranges between (24.3s to 29.7s) and the accuracy rate for gesture types varies between (88.7s to 92.5s). Moreover, the simulation results indicated that real time voting using our proposed system generated 100% precision and 99% recall. Our system showed high accuracy in gesture recognition and profound security when using Equal Error Rate quality measure. Different to other approaches, the interface of our proposed system, designed for a wide audience of users, greatly simplifies the voting process.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】Blockchains; Security; Authentication; Electronic voting systems; Smart contracts; Older adults; Electronic voting; Gesture recognition; User interfaces; Blockchain; electronic voting; gesture recognition; accessibility; security; user interface
【发表时间】2024
【收录时间】2024-10-28
【文献类型】 案例研究
【Author】 Ullah, Zia Waheed, Abdul Ismail Mohmand, Muhammad Basar, Sadia Zareei, Mahdi Granda, Fausto
【影响因子】3.476
【主题类别】
区块链应用-实体经济-网络安全
【Abstract】Artificial intelligence (AI) is one of the key technologies emerging in the Industrial Revolution that could protect against cybersecurity threats. AI is a key component of big data analytics and enables accurate real-time data analysis. AI can analyze big data, but it has some issues with security, privacy, and centralization of data. Moreover, cybercriminals continue to advance, so law enforcement faces more threats. With traditional cybersecurity solutions, sophisticated cyber-attacks are harder to detect and defend against. In complex cyberspaces, AI algorithms mine valuable features from data. However, the data on the Internet is scattered and controlled by different parties, making it challenging to authorize and validate its use. The AICyber-Chain model is presented in this paper for securely storing, calculating, and distributing data on the Internet at an enterprise scale. In a large-scale Internet environment, our proposed AICyber-Chain model integrates three key components to ensure a more secure cyberspace, enhancing AI, namely: Firstly, blockchain-based data sharing guarantees ownership at a large scale, enabling real-time data sharing. Secondly, a platform powered by AI makes cyberspace more trustworthy. Thirdly, sharing data or services rewards participants financially, which promotes sharing. We also discuss a typical use scenario, an alternative deployment method, and its security and commercial efficacy. Also, we simulated our model on Ethereum's official test network, called Rinkeby, to demonstrate its practicality and efficiency. This model speeds up authentication by 1.8 times compared to the centralized model. In addition, our proposed solution reduces gas consumption by 20 to 25%. Our paper aims to serve as a guide and reference point for cybersecurity researchers and industry practitioners, especially from an intelligent computing or AI-based technical standpoint.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】Artificial intelligence; Blockchains; Computer security; Security; Data models; Machine learning; Cyberspace; Artificial intelligence (AI); blockchain-based cybersecurity; AI in cybersecurity; data security; cyberspace security
【发表时间】2024
【收录时间】2024-10-28
【文献类型】 理论模型
【影响因子】3.476
【主题类别】
区块链应用-虚拟经济-Web3
【Abstract】In Cognitive Radio (CR) networks combined with Energy Harvesting (EH) technology, Secondary Users (SUs) are vulnerable to jamming attacks when sensing idle channels. At the same time, they may encounter numerous jamming and eavesdropping attacks during the data transmission phase. This paper examines the scenario in which SUs are susceptible to malicious attacks and energy constraints in both the sensing and transmission phases. We propose a utility function applicable to a single time slot. The blockchain uses Smart Contract (SC) technology to set rewards and punishments for users' channel selection behavior and adjust mining difficulty. This method combines blockchain with spectrum sensing data fusion, abandons the decision-making mechanism of the traditional Cooperative Spectrum Sensing (CSS) Fusion Center (FC), and adopts a distributed structure to ensure the security and reliability of sensing data fusion. In addition, this paper uses the potential game and the Stackelberg game to study the optimal transmission channel and optimal time slot allocation strategy for SUs under malicious attacks. Considering the possible interference caused by channel switching and the greedy principle of Malicious User (MU), the proposed two-layer game method gradually optimizes the sensing detection probability and secure communication rate with time slot iteration. In order to further improve the secure communication rate, an iterative update formula for transmission power is given to make reasonable use of the remaining energy of each SU at the end of each time slot. Simulation results show that the proposed method is superior to traditional methods in both sensing performance and secure communication rate.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】Sensors; Jamming; Games; Security; Eavesdropping; Blockchains; Probability; Power system reliability; Full-duplex system; Throughput; Energy harvesting; jamming attack; eavesdropping attack; two-layer game; blockchain
【发表时间】2024
【收录时间】2024-10-28
【文献类型】 案例研究
【影响因子】3.476
【主题类别】
区块链技术-核心技术-加密算法
【Abstract】Blockchain technology has ushered in a transformative paradigm of decentralized and transparent systems, offering innovative solutions across diverse sectors. While these systems strive for unparalleled transparency and trustlessness in a fully distributed framework, permissionless blockchains, such as Bitcoin and Ethereum, encounter vulnerabilities due to their intrinsically public nature. Addressing these vulnerabilities, the emergence of permissioned blockchains presents a fortified alternative, incorporating rigorous access controls and authentication protocols to ensure participation exclusivity and transaction confidentiality. Nevertheless, a keen observation reveals that, despite encryption, the operational traffic within these blockchains manifests distinct time-series patterns and operational relations during sensitive data exchanges. Such patterns hold the potential to inadvertently expose critical details about the network, encompassing its topology and the operational dependencies among nodes. In light of this revelation, we introduce a pioneering blockchain fingerprinting mechanism, denoted as gShock. This system meticulously analyzes periodic patterns and the context of operational relations from the collected blockchain network traffic. It employs a Graph Neural Network (GNN)-based model, adept at capturing the intricate characteristics innate to specialized blockchain operations. Through empirical experiments conducted in a realistic permissioned blockchain environment, comprising various nodes, we ascertain that gShock demonstrates a remarkable proficiency in classifying blockchain operational traffic with an F1-score of >= 96 % and identifying individual dependencies with a macro F1-score of >= 93 %.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】Blockchains; Peer-to-peer computing; Fingerprint recognition; Feature extraction; Organizations; Smart contracts; Open source software; Graph neural networks; Bitcoin; Wide area networks; Blockchain security; fingerprinting; graph neural network (GNN)
【发表时间】2024
【收录时间】2024-10-28
【文献类型】 案例研究
CCF-A
【影响因子】3.183
【主题类别】
区块链技术-核心技术-拜占庭协议
【Abstract】In Byzantine fault-tolerant (BFT) systems, maintaining consistency amidst malicious replicas is crucial, especially for blockchain systems. Recent innovations in this field have integrated multiple leaders into the BFT consensus mechanism to boost scalability and efficiency. However, the existing approaches often lead to excessive consumption of storage, bandwidth, and CPU resources due to redundant transactions. And the attempting to mitigate resource wastage inadvertently reduces resilience against Byzantine failures. To this end, we propose PeterHofe, an innovative ring-based approach for collaborative transaction processing. PeterHofe focuses on balancing resource utilization and minimizing the influence of Byzantine leaders, thereby enhancing transaction processing speed and overall system reliability. PeterHofe innovates by partitioning the transaction hash space into various buckets and creating a complex mappings between these buckets and the replicas, effectively reducing the control of Byzantine replicas. In developing PeterHofe, we concentrate on three primary objectives: 1) the creation of a permutation-based ring structure that enhances resistance to Byzantine censorship, backed by thorough mathematical proofs and analyses; 2) the development of a Prophecy-Implementation mechanism aimed at minimizing transaction replication while scrutinizing potential malicious activities; 3) to ensure the applicability of our proposed method across various types of multi-leader BFT consensus protocols, we have developed an additional asynchronous protocol to ensure consistent application of the packaging strategy. We have implemented PeterHofe using the latest significant frameworks, Narwhal and Tusk, and our empirical results affirm its capability to simultaneously minimize resource waste and bolster system robustness. Specifically, PeterHofe demonstrates efficiency in resource utilization, achieving a 20-fold reduction of resource waste when compared to the Random-based Strategy. When against the advanced Hash-based Partitioning Strategy, it reduces malicious transaction control by at least 66%, leading to up to 75% lower latency. In scenarios of high traffic, our approach significantly outperforms existing strategies in throughput. Against the Random-based Strategy, it achieves a 6.11% increase, and when compared to the Hash-based Partitioning Strategy, the improvement is 20%.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】Packaging; Collaboration; Fault tolerant systems; Resource management; Consensus protocol; Censorship; Throughput; Blockchain; BFT; multi-leader; transaction packaging
【发表时间】2024
【收录时间】2024-10-28
【文献类型】 理论模型
【DOI】 10.1109/TC.2024.3398510
【Author】 Zhang, Yin Zhang, Menglong Wu, Liming Li, Jin
【影响因子】2.921
【主题类别】
区块链应用-实体经济-教育领域
【Abstract】Rapid advancements in the information age have prompted significant digitalization in global higher education, with Chinese higher education particularly adapting to the influence of artificial intelligence. This study focuses on the digital transformation in China's higher education, specifically within AI-assisted engineering education. It examines the digitalization of classrooms, expansion of teaching elements, and redesign of educational dynamics, while highlighting digital innovations in teaching methodologies and the integration of AI systems. Using the Engineering Cost Estimation as a case study, the paper showcases the practical application of AI in engineering education in China. The findings reveal the interplay between external societal, economic, political, and technological factors and internal academic aspects like curriculum quality. The study addresses the digital divide, advocates for equitable technology access, and emphasizes digital literacy as crucial in the twenty-first century. It predicts significant structural changes in universities, proposing borderless educational environments and flexible, interdisciplinary approaches, alongside a blockchain-based credit system.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】
【发表时间】2024
【收录时间】2024-10-28
【文献类型】 案例研究
【影响因子】2.557
【主题类别】
区块链技术-核心技术-智能合约
【Abstract】Access control for smart contracts is the primary security mechanism for protecting users' digital assets. However, existing solutions have defects in control granularity and flexibility, and a large number of resource-constrained blockchain nodes impose stringent and lightweight requirements on access control mechanisms. Therefore, achieving secure, efficient, and flexible access control for smart contracts has become a key issue that blockchain applications need to address. Based on the attribute-based access control model, this paper utilizes attribute-based signature (ABS) to achieve flexible and efficient access control for smart contracts. First, to solve the problem that existing ABS schemes are not suitable for resource-constrained blockchain nodes because they are mainly based on expensive bilinear pairing, a lightweight no-pairing attribute-based signature scheme called LABS is designed to make the signature size independent of the user's attribute set and decouple the signature from the verification policy. Then, based on the LABS scheme, a smart contract-oriented access control mechanism (DSCABS) is proposed to ensure that only legitimate users whose attributes satisfy the access policy can be authorized to invoke smart contracts. Also, DSCABS supports dynamic updates of user rights and contract access policies without modifying or redeploying the smart contract. Finally, the effectiveness of the proposed scheme is verified by simulation experiments.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】Smart contract; Access control; ABAC model; Attribute-based signature
【发表时间】2025
【收录时间】2024-10-28
【文献类型】 案例研究
【影响因子】0.896
【主题类别】
区块链应用-实体经济-农业领域
【Abstract】Smart agriculture leverages human intelligence and artificial intelligence in digital farming, which heavily relies on data collection, analysis, and decision support delivery. Farmers need reliable data and a decision support system to make accurate decisions and take appropriate actions. The Internet of Things (IoT) not only creates the backbone for farm data collection for intelligent farming but also brings some security concerns to the agriculture field. Though many studies exist on security in agriculture, particularly device identification and tracking, cryptography, blockchain, and other security approaches, the concerns about agricultural data integrity have not been fully explored in the current literature. Data integrity threats could cause huge losses to farmers, threatening food security, especially in developing countries. Given the early stage of development in the domain and the rapid adoption ofIoT, ensuring the trustworthiness of data from various devices poses a significant challenge. This challenge is exacerbated in wireless sensor network scenarios, particularly in harsh environments where potential avenues for physical attacks exist. This article evaluates a data integrity threat detection technique in an IoT wireless network. It proposes an approach to identify potential data integrity failures or threats. The effectiveness of this approach is demonstrated through an empirical use-case study focusing on agriculture applications. Through experimental and trace-based simulations, we illustrate that threats can potentially be identified with a 91% accuracy rate and approximately 98% precision and recall. The proposed solution could be deployed in distributed and centralized digital agricultural systems to identify and predict real-time data integrity issues or threats.
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【Keywords】Collaborative filtering; Data integrity threats; Local outlier factor; Smart agriculture.; vehicles (UAV); sensors; machine learning; artificial
【发表时间】2024
【收录时间】2024-10-28
【文献类型】 案例研究
【DOI】 10.13031/aea.16029