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2024年07月21日 18篇

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BCAE: A Blockchain-Based Cross Domain Authentication Scheme for Edge Computing

【Author】 Zhang, Shiwen Yan, Ziwei Liang, Wei Li, Kuan-Ching Di Martino, Beniamino

CCF-C

【影响因子】10.238

【主题类别】

区块链应用-实体经济-物联网

【Abstract】With the vigorous development of the Internet of Things (IoT), mobile users need to access data from other domains in edge computing. To achieve secure data sharing, mobile users first need to be authenticated by servers from different domains and then negotiate session keys among them. However, traditional schemes cannot solve cross-domain identity authentication and key agreement problems well due to the limited computational resources of IoT devices. In this work, we propose a blockchain-based cross-domain authentication scheme for Edge computing, namely, BCAE. First, to achieve secure identity verification, we design a novel cross-domain mutual identity authentication algorithm based on digital certificates and digital signatures. Next, to improve efficiency, we utilize the blockchain to share information among different domains to reduce the computation overhead. To realize quick key agreement, we apply the elliptic curve cryptography technique to design a lightweight key agreement algorithm and obtain secure session keys. Extensive experiments conducted on an actual smart healthcare issue to validate the performance of BCAE and formal security analysis confirmed the potential of the proposed work.

你可以尝试使用大模型来生成摘要 立即生成

【Keywords】Authentication; Blockchains; Security; Internet of Things; Edge computing; Protocols; Privacy; Blockchain; cross-domain authentication; edge computing; key agreement

【发表时间】2024

【收录时间】2024-07-21

【文献类型】 实验仿真

【DOI】 10.1109/JIOT.2024.3387934

Evolutionary Medical Data Modeling and Sharing via Federated Learning Over Sharded Blockchain

【Author】 Zhang, Mengyao Lin, Feilong Tian, Lei Jia, Riheng Zheng, Zhonglong Li, Minglu

CCF-C

【影响因子】10.238

【主题类别】

区块链应用-实体经济-医疗领域

【Abstract】Linking medical data silos for medical model learning and sharing makes for better healthcare for humanity. Before that, two critical issues must be solved, i.e., patient privacy protection and data contributors' rights and interests. This article proposes an evolutionary medical data modeling and sharing (EMDMS) framework. Specifically, EMDMS adopts a federated learning (FL) scheme to coordinate the decentralized medical model learning and model aggregation without the leakage of raw data. A dual-loop FL mechanism with a tailored control strategy is developed for the realization of evolutionary model learning with the consideration of the ever-growing medical data. Then, a long-term pricing and revenue distribution strategy is designed for evolutionary model sharing, thus to make the medical model self-growth. It not only ensures fair benefits for data contributors but also enables low-cost sharing of models for public welfare. EMDMS runs on the sharded blockchain to support parallel tasks where dedicated smart contracts are implemented for EMDMS to guarantee security and trustworthiness. A prototype system with simulations on the Fed-ISIC2019 data set demonstrates the effectiveness of EMDMS and its advantages over some existing typical solutions.

你可以尝试使用大模型来生成摘要 立即生成

【Keywords】Blockchain (BC); evolutionary mechanism; federated learning (FL); medical data modeling; pricing

【发表时间】2024

【收录时间】2024-07-21

【文献类型】 实验仿真

【DOI】 10.1109/JIOT.2024.3389593

Trusted Authentication Mechanism of IoT Terminal Based on Authorization Consensus and Reputation Evaluation

【Author】 Rui, Lanlan Zhao, Liangchen Yan, Jingyang Qiu, Xuesong Guo, Shaoyong

CCF-C

【影响因子】10.238

【主题类别】

区块链技术-协同技术-物联网

【Abstract】With the deep integration of a new generation of information technology and physical manufacturing, equipment in all walks of life and fields has transformed to digitalization, networking, and intelligence, and the Internet of Things puts forward higher requirements for ubiquitous interconnection, security, reliability, intelligence, and efficiency. The data interaction of IoT terminal devices has cross-system, cross-enterprise, and cross-business requirements, but this also leads to many sensitive information in the Internet of Things network, such as hidden leakage and difficulty in distinguishing the authenticity of data information. Based on the above challenges, this article proposes a distributed authentication scheme based on Delegated Proof of Stake consensus algorithm and a dynamic reputation evaluation mechanism based on smart contracts, which improves the authentication efficiency and the anti-attack ability of the authentication network and maintains the security and stability of the network. At the same time, the dynamic reputation evaluation results are uploaded to the blockchain storage, which not only ensures the security and immutability of data but also provides queryable historical reputation records for subsequent terminal access authentication evaluation. Safety analysis and performance simulation experiments show that the proposed scheme has high safety and good performance.

你可以尝试使用大模型来生成摘要 立即生成

【Keywords】Authentication; Internet of Things; Security; Smart contracts; Performance evaluation; Certification; Heuristic algorithms; Access authentication; blockchain; trusted networks

【发表时间】2024

【收录时间】2024-07-21

【文献类型】 实验仿真

【DOI】 10.1109/JIOT.2024.3387448

Revenue-Optimal Contract Design for Content Providers in IoT-Edge Caching

【Author】 Li, Hongtao Chen, Ying Yang, Yaozong Huang, Jiwei

CCF-C

【影响因子】10.238

【主题类别】

区块链技术-协同技术-物联网

【Abstract】Edge caching is crucial in the Internet of Things (IoT) by accelerating content delivery and reducing latency, offering significant advantages. However, inappropriate incentive mechanisms may prevent third-party edge caching nodes from caching data. To address the incentive challenges in edge caching, this article proposes a contract theory approach to resolve the incentive issues between content providers (CPs) (Google and Microsoft) and edge caching nodes. Initially, utilizing the framework of contract theory, the security service quality of edge caching nodes is classified into a finite number of types, and transactions between CPs and edge caching nodes are modeled. Subsequently, contract packages containing popular data content and corresponding rewards are designed for different types of edge caching nodes. Utilizing the revelation principle of contract theory addresses the problem of incomplete information in the system, enabling CPs to maximize revenue. A blockchain-based reputation mechanism is employed to identify abnormal nodes within edge caching nodes. Numerical results demonstrate that, compared to other mechanisms, our proposed contracts can effectively incentivize the participation of edge caching nodes, significantly enhance CPs' revenue, and improve content delivery efficiency and effectiveness.

你可以尝试使用大模型来生成摘要 立即生成

【Keywords】Contract design; edge caching; game analysis; Internet of Things (IoT)

【发表时间】2024

【收录时间】2024-07-21

【文献类型】 实验仿真

【DOI】 10.1109/JIOT.2024.3385446

Attribute-Based Access Control Scheme for Secure Identity Resolution in Prognostics and Health Management

【Author】 He, Yunhua Yan, Zihe Yuan, Tingli

CCF-C

【影响因子】10.238

【主题类别】

区块链应用-实体经济-健康领域

【Abstract】In modern industrial enterprises, the application of identity resolution systems contributes to improving efficiency and simplifying production management. With the development of the Industrial Internet of Things (IIoT), integrating identity resolution and prognostics and health management (PHM) has become a new trend. However, ensuring the confidentiality and integrity of enterprise identity data has become challenging due to flaws in identifier encoding design and the semi-trusted nature of identity resolution platforms. To address these issues, we propose a fine-grained access control scheme for the identity resolution system. Our scheme utilizes a novel identifier encoding method and attribute-based encryption algorithm, enabling flexible data classification and permission management for industry enterprises. Moreover, to combat potential malicious behaviors by users, such as unauthorized access or identity abuse, we leverage Blockchain technology to trace malicious users while safeguarding user privacy. The security of our scheme is formally proven under the decisional bilinear Diffie-Hellman (DBDH) assumption. Comparative experiments demonstrate the advantages of our proposal in terms of time costs and storage overhead over alternative schemes.

你可以尝试使用大模型来生成摘要 立即生成

【Keywords】Access control; attribute-based encryption (ABE); blockchain; identity resolution; industrial Internet; prognostics and health management (PHM)

【发表时间】2024

【收录时间】2024-07-21

【文献类型】 实验仿真

【DOI】 10.1109/JIOT.2024.3387079

Futuristic Decentralized Vehicular Network Architecture and Repairing Management System on Blockchain

【Author】 Arshad, Usama Halim, Zahid Alasmary, Hisham Waqas, Muhammad

CCF-C

【影响因子】10.238

【主题类别】

区块链应用-实体经济-车联网

【Abstract】Blockchain technology is used often as a merger with other technologies to achieve a high level of security, privacy, and robustness and to handle issues, such as maliciousness of nodes, privacy leakage, the selfishness of nodes, communication delays, and high execution and transaction costs. There is currently a lack of a comprehensive system for automating and cost-effectively managing vehicle repairs, maintenance, and other associated services. To solve such issues, we proposed a novel futuristic comprehensive model that integrates a blockchain-based framework to safely record vehicle maintenance, validate repair services, and oversee parts inventory. It employs smart contracts and consensus protocols to secure communications and data storage, thus reducing data breaches and vulnerabilities from single-point failures. A reward system is embedded within the network to encourage positive behavior and deter detrimental actions. We also incorporated advanced privacy-ensuring methods, like zero-knowledge proofs and secure multiparty computation, to safeguard sensitive data while preserving its utility. Our model features automatic detection and response mechanisms for node failure, improving network resilience by 25% thus also providing a 20% reduction in execution, operational costs, and scalability with an enhancement of 15%, underscoring the model's efficiency in vehicular repair and maintenance activities. Results and simulations clearly depict the overall performance and efficiency in terms of security, privacy, node failure, and the management of vehicle repairs with respect to other closely related models.

你可以尝试使用大模型来生成摘要 立即生成

【Keywords】Blockchains; Maintenance engineering; Security; Privacy; Maintenance; Scalability; Internet of Things; 5G; blockchain; decentralized autonomous organization (DAO); incentive; intelligent transportation systems (ITS); repairing; vehicle network authority (VNA)

【发表时间】2024

【收录时间】2024-07-21

【文献类型】 实验仿真

【DOI】 10.1109/JIOT.2024.3386600

Lifecycle Optimization of Smart Contract for Different Scenarios in 6G Network

【Author】 Su, Hong Guo, Bing Suo, Xinhua Zhang, Chuanfeng

CCF-C

【影响因子】10.238

【主题类别】

区块链技术-协同技术-6G

【Abstract】In the rapidly evolving landscape of the sixth generation (6G) network, smart contracts emerge as a pivotal technology for enforcing trustful rules. However, the conventional lifecycle model of smart contracts-encompassing stages from initiation to the termination of a contract instance-suffers from rigidity and lack of customization, leading to notable operational challenges. These challenges primarily manifest as heightened resource demands, including longer waiting periods and escalated transaction costs, which hinder the adaptability of smart contracts in the varied and dynamic contexts of 6G-connected environments. Driven by these issues, this article conducts a comprehensive analysis of the smart contract lifecycle. We introduce an innovative lifecycle model that offers customizable flexibility, allowing for the merging or separation of different stages in the smart contract process. Meanwhile, we propose a unique transaction data structure designed to integrate parameters of combined stages, each marked with distinct identifiers for differentiation. Further, we introduce an innovative address scheme for smart contract instances, which provides an identifier to simplify instance access while also maintaining a mechanism for traditional access methods. The verification results show that the model can save 52.72% of processing fee and 68.09% of completion time compared with the conventional method.

你可以尝试使用大模型来生成摘要 立即生成

【Keywords】Deployment; lifecycle optimization; sixth generation (6G) network; smart contract

【发表时间】2024

【收录时间】2024-07-21

【文献类型】 实验仿真

【DOI】 10.1109/JIOT.2024.3384239

Are cryptos different? Evidence from retail trading

【Author】 Kogan, Shimon Makarov, Igor Niessner, Marina Schoar, Antoinette

FT50 UTD24

【影响因子】8.238

【主题类别】

区块链治理-市场治理-价格预测

【Abstract】Trading in cryptocurrencies grew rapidly over the last decade, dominated by retail investors. Using data from eToro, we show that retail traders are contrarian in stocks and gold, yet the same traders follow a momentum-like strategy in cryptocurrencies. The differences are not explained by individual characteristics, investor composition, inattention, differences in fees, or preference for lottery-like assets. We conjecture that retail investors have a model where cryptocurrency price changes affect the likelihood of future widespread adoption, which leads them to further update their price expectations in the same direction.

你可以尝试使用大模型来生成摘要 立即生成

【Keywords】Cryptocurrencies FinTech Retail trading Social finance

【发表时间】2024

【收录时间】2024-07-21

【文献类型】 实证数据

【DOI】 10.1016/j.jfineco.2024.103897

Tail connectedness of DeFi and CeFi with accessible banking pillars: Unveiling novel insights through wavelet and quantile cross-spectral coherence analyses

【Author】 Asl, Mahdi Ghaemi Ben Jabeur, Sami

【影响因子】8.235

【主题类别】

区块链治理-市场治理-DeFi

【Abstract】This study evaluates the interplay between decentralized finance (DeFi) and centralized finance (CeFi) within the realm of inclusive banking by examining their foundational components, namely, alternative finance industry, distributed ledger platforms, and future payment technologies. The alternative finance industry leverages innovative technologies, such as direct lending, crowdfunding, automated wealth management, on-demand insurance, and digital currencies. This feature aligns well with the DeFi principles, and it is also beneficial to CeFi. Distributed ledger platforms offer transparency and security for both DeFi and CeFi, whereas future payment technologies provide user-friendly solutions. This study applies novel wavelet and quantile cross-spectral coherence analyses to obtain nuanced relationship insights. This methodology categorizes crypto finance into the DeFi and broader cryptocurrency ecosystems to facilitate robust comparison with traditional banking. It further delineates democratized banking into alternative financing mechanisms, distributed ledger technologies, and future payment capabilities. Wavelet coherence analysis reveals time-frequency associations, whereas quantile cross-spectral coherence unveils extreme connections under different market conditions. The findings suggest the existence of dynamic relationships between inclusive banking components and various financial infrastructures. These relationships vary across return distributions and time scales. In regular markets, positive associations are seen in yearly and monthly frequency cycles with alternative finance and centralized services exhibiting the strongest linkage. During periods of extremely high returns, CeFi and centralized-decentralized (hybrid) infrastructures exhibit limited interconnectivity with democratized banking. Moreover, DeFi's association with distributed ledger technology is negligible. In bear markets, the strongest positive associations are observed between inclusive access and conventional, hybrid, and decentralized financial systems. These insights provide new perspectives on the dynamics between financial systems during extreme conditions. This study emphasizes the need for adaptive regulation, international cooperation, and a balance between innovation and stability to protect and empower users. Collaboration between academia and policymakers is essential to navigate this evolving landscape and advance democratized banking.

你可以尝试使用大模型来生成摘要 立即生成

【Keywords】Decentralized finance (DeFi); Centralized finance (CeFi); Democratized banking ecosystem; Alternative finance industry; Wavelet and quantile analyses

【发表时间】2024

【收录时间】2024-07-21

【文献类型】 实证数据

【DOI】 10.1016/j.irfa.2024.103424

Deep learning systems for forecasting the prices of crude oil and precious metals

【Author】 Foroutan, Parisa Lahmiri, Salim

【影响因子】6.793

【主题类别】

区块链治理-市场治理-价格预测

【Abstract】Commodity markets, such as crude oil and precious metals, play a strategic role in the economic development of nations, with crude oil prices influencing geopolitical relations and the global economy. Moreover, gold and silver are argued to hedge the stock and cryptocurrency markets during market downsides. Therefore, accurate forecasting of crude oil and precious metals prices is critical. Nevertheless, due to the nonlinear nature, substantial fluctuations, and irregular cycles of crude oil and precious metals, predicting their prices is a challenging task. Our study contributes to the commodity market price forecasting literature by implementing and comparing advanced deep-learning models. We address this gap by including silver alongside gold in our analysis, offering a more comprehensive understanding of the precious metal markets. This research expands existing knowledge and provides valuable insights into predicting commodity prices. In this study, we implemented 16 deep- and machine-learning models to forecast the daily price of the West Texas Intermediate (WTI), Brent, gold, and silver markets. The employed deep-learning models are long short-term memory (LSTM), BiLSTM, gated recurrent unit (GRU), bidirectional gated recurrent units (BiGRU), T2V-BiLSTM, T2V-BiGRU, convolutional neural networks (CNN), CNN-BiLSTM, CNN-BiGRU, temporal convolutional network (TCN), TCN-BiLSTM, and TCN-BiGRU. We compared the forecasting performance of deep-learning models with the baseline random forest, LightGBM, support vector regression, and k-nearest neighborhood models using mean absolute error (MAE), mean absolute percentage error, and root mean squared error as evaluation criteria. By considering different sliding window lengths, we examine the forecasting performance of our models. Our results reveal that the TCN model outperforms the others for WTI, Brent, and silver, achieving the lowest MAE values of 1.444, 1.295, and 0.346, respectively. The BiGRU model performs best for gold, with an MAE of 15.188 using a 30-day input sequence. Furthermore, LightGBM exhibits comparable performance to TCN and is the best-performing machine-learning model overall. These findings are critical for investors, policymakers, mining companies, and governmental agencies to effectively anticipate market trends, mitigate risk, manage uncertainty, and make timely decisions and strategies regarding crude oil, gold, and silver markets.

你可以尝试使用大模型来生成摘要 立即生成

【Keywords】Crude oil forecasting; Precious metal forecasting; Deep learning; Temporal convolutional networks; Time2Vector; LightGBM

【发表时间】2024

【收录时间】2024-07-21

【文献类型】 实证数据

【DOI】 10.1186/s40854-024-00637-z

Towards a distributed nodes selection mechanism for federated to blockchain-based IoT

【Author】 Abdmeziem, Mohammed Riyadh Akli, Hiba Zourane, Rima Nacer, Amina Ahmed

【影响因子】5.711

【主题类别】

区块链技术-协同技术-联邦学习

区块链技术-协同技术-物联网

【Abstract】Integrating blockchain (BC) with Federated Learning (FL) shows promise but presents challenges, particularly in the selection of the most appropriate IoT nodes for sensitive tasks. Existing Artificial Intelligence (AI) based approaches are tailored to dynamic environments, but they are complex and resource-intensive. On the other hand, score-based methods are faster to implement but lack flexibility. In this paper, we propose a two-step hybrid solution which uses the reputation score approach to train a DRL model, creating a framework that combines the efficiency of deterministic methods with the adaptability of AI-based solutions. In fact, we designed a score-based method relying on devices attributes and behavior making the system operational from the outset. Also, this allows the gathering of relevant real-time data for training the DRL model. Besides, the variations in the performances of IoT devices pose a challenge in achieving synchronous aggregation. To address this, we designed a multi-level aggregation mechanism, which allows local models to be uploaded to the BC, where an aggregator is in charge of validation. The validated models are then aggregated into intermediate models. This process continues until a global model is formed. To evaluate our approach, we created several simulation scenarios including the number of nodes to assess scalability, the dropout rate to estimate availability, and the percentage of malicious nodes to evaluate the robustness of the system against attacks. These experiments aimed to demonstrate the effectiveness of our approach. The obtained results are promising highlighting its robustness and flexibility showing improved performance, security, and availability.

你可以尝试使用大模型来生成摘要 立即生成

【Keywords】Internet of Things (IoT); Federated learning (FL); Blockchain (BC); Nodes selection; Deep reinforcement learning (DRL); Asynchronicity

【发表时间】2024

【收录时间】2024-07-21

【文献类型】 实验仿真

【DOI】 10.1016/j.iot.2024.101276

ANFIS optimization-based watermarking for securing integrity of medical images with blockchain authentication

【Author】 Awasthi, Divyanshu Khare, Priyank Srivastava, Vinay Kumar Singh, Amit Kumar

【影响因子】4.152

【主题类别】

区块链应用-实体经济-医疗领域

【Abstract】In the current scenario, medical records (MR) transmission has become a popular way for smart healthcare systems to provide suitable treatment to several patients. Confidentiality of MR is a concerning issue that needs to be taken care of with an effective approach. Therefore, to provide a suitable remedial action against these undesirable security issues, a watermarking technique is used. Thus, this paper presents a secured novel watermarking technique that uses salient features of redundant discrete wavelet transform (RDWT), multiresolution singular value decomposition (MSVD), and adaptive neuro-fuzzy inference system (ANFIS). This method involves the computation of a medical image 's region of interest (ROI) through an ROI-based filtering approach. A hybrid watermark is generated with Aadhar and barcode images embedded into the transformed cover medical image. ANFIS plays a vital role in deciding the optimal value of the embedding strength, facilitating a proper trade-off among different characteristics. Blockchain encryption is also carried out to authenticate the hybrid watermark using this approach. This authentication feature aids in protecting vital medical data, which ensures better copyright protection. Experimental analysis remarkably illustrates the robustness and imperceptibility of the proposed technique.

你可以尝试使用大模型来生成摘要 立即生成

【Keywords】Confidentiality; MSVD; RDWT; ANFIS; Optimization

【发表时间】2024

【收录时间】2024-07-21

【文献类型】 实证数据

【DOI】 10.1016/j.compeleceng.2024.109451

Improving Blockchain Consistency Bound by Assigning Weights to Random Blocks

【Author】 Gong, Xueping Zhang, Qing Li, Huizhong Zhang, Jiheng

FT50 UTD24

【影响因子】3.924

【主题类别】

区块链技术-协同技术-共识机制

【Abstract】Blockchains based on the celebrated Nakamoto consensus protocol have shown promise in several applications, including cryptocurrencies. However, these blockchains have inherent scalability limits caused by the protocol's consensus properties. In particular, the consistency property demonstrates a tight trade-off between block production speed and the system's security in terms of resisting adversarial attacks. As such, this paper proposes a novel method called Ironclad, which improves the blockchain consistency bound by assigning a different weight to randomly selected blocks. We apply our method to the original Nakamoto protocol and rigorously prove that such a combination can significantly improve the consistency bound by analyzing the fundamental consensus properties. This kind of improvement enables a much faster block production rate than the original Nakamoto protocol but with the same security guarantee.

你可以尝试使用大模型来生成摘要 立即生成

【Keywords】Markov process; consensus; blockchain

【发表时间】2024

【收录时间】2024-07-21

【文献类型】 实证数据

【DOI】 10.1287/opre.2022.0463

Federated Learning-Based Prediction of Energy Consumption from Blockchain-Based Black Box Data for Electric Vehicles

【Author】 Park, Jong-Hyuk Joe, In-Whee

【影响因子】2.838

【主题类别】

区块链应用-实体经济-数据管理

【Abstract】In modern society, the proliferation of electric vehicles (EVs) is continuously increasing, presenting new challenges that necessitate integration with smart grids. The operational data from electric vehicles are voluminous, and the secure storage and management of these data are crucial for the efficient operation of the power grid. This paper proposes a novel system that utilizes blockchain technology to securely store and manage the black box data of electric vehicles. By leveraging the core characteristics of blockchain-immutability and transparency-the system records the operational data of electric vehicles and uses federated learning (FL) to predict their energy consumption based on these data. This approach allows the balanced management of the power grid's load, optimization of energy supply, and maintenance of grid stability while reducing costs. Additionally, the paper implements a searchable black box data storage system using a public blockchain, which offers cost efficiency and robust anonymity, thereby enhancing convenience for electric vehicle users and strengthening the stability of the power grid. This research presents an innovative approach to the integration of electric vehicles and smart grids, exploring ways to enhance the stability and energy efficiency of the power grid. The proposed system has been validated through real data and simulations, demonstrating its effectiveness and performance in managing black box data and predicting energy consumption, thereby improving the efficiency and stability of the power grid. This system is expected to empower electric vehicle users with data ownership and provide power suppliers with more accurate energy demand predictions, promoting sustainable energy consumption and efficient power grid operations.

你可以尝试使用大模型来生成摘要 立即生成

【Keywords】electric vehicles; blockchain; federated learning; energy management; data security; machine learning

【发表时间】2024

【收录时间】2024-07-21

【文献类型】 实验仿真

【DOI】 10.3390/app14135494

Trust attack prevention based on Spark-blockchain in social IoT: a survey

【Author】 Masmoudi, Mariam Amous, Ikram Zayani, Corinne Amel Sedes, Florence

【影响因子】2.427

【主题类别】

区块链技术-协同技术-物联网

【Abstract】Integrating the Internet of Things (IoT) with Social Networks (SN) has given rise to a new paradigm called Social IoT, which allows users and objects to establish social relationships. Nonetheless, trust issues such as attacks have emerged. These attacks can influence service discovery results. A trust management mechanism has become a major challenge in the Social IoT to prevent these attacks and ensure qualified services. A few studies have addressed trust management issues, especially those that prevent trust attacks in Social IoT environments. However, most studies have been dedicated to detect offline attacks with or without specifying the type of attack performed. These works will not be able to prevent attacks by aborting transactions between users because their primary purpose is to detect an offline attack. In addition, they do not consider security properties. This research paper aims to provide a detailed survey on trust management mechanism to handle trust attacks in Social IoT. In this research paper, we compared the techniques and technologies whose common point is attack prevention and demonstrated that blockchain technology can play a key role in developing a trust management mechanism that can prevent trust attacks while maintaining security properties. Then, we proposed combining the Apache Spark Framework with blockchain technology to provide real-time attack prevention. This combination can assist in creating upgraded trust management mechanisms in Social IoT environments. These mechanisms aim to prevent attacks in real-time through considering the security properties. Lack of survey papers in the area of trust attack prevention in real-time stands for an important motivational factor for writing this paper. The current research paper highlights the potential of the blockchain technology and Apache Spark in terms of developing an upgraded trust management able to prevent trust attacks in real-time.This paper provides a comprehensive survey on trust management mechanisms and approaches to handle trust attacks in Social IoT. Lack of such papers increases the significance of this paper. It also offers potential future research directions in terms of real-time trust attack prevention.

你可以尝试使用大模型来生成摘要 立即生成

【Keywords】Internet of Things (IoT); Social IoT; Trust; Trust attack prevention; Real-time; Blockchain; Stream processing; Apache Spark

【发表时间】2024

【收录时间】2024-07-21

【文献类型】 综述

【DOI】 10.1007/s10207-024-00885-1

Enhancing healthcare security: Time-based authentication for privacy-preserving IoMT sensor monitoring framework leveraging blockchain technology

【Author】 Sharma, Aashima Kaur, Sanmeet Singh, Maninder

【影响因子】1.831

【主题类别】

区块链技术-协同技术-物联网

【Abstract】The rapid progression of the Internet of Things and its increasing use in healthcare has generated considerable concerns over the safeguarding and privacy of vital medical data. In response to these issues, blockchain has surfaced as a possible remedy, offering transparent, immutable, and decentralized storage. Nevertheless, conventional blockchain-based systems still encounter constraints in maintaining anonymity, confidentiality, and privacy. Hence, this article suggests a framework based on a secure consortium blockchain that prioritizes data privacy and employs time-based authentication to streamline patient data monitoring. First, we employ time-based authentication to verify the identities of authorized users. This process utilizes the NIK-512 hashing algorithm in conjunction with passwords and registered timestamps, which strengthens the confidentiality of data. Patient information undergoes encryption before transmission within the network. Further, our framework introduces a sensor registration service that the trusted node employs to assign a distinct identity to each sensor connected to a patient. The implementation of data processing and filtering techniques at the edge layer serves the purpose of mitigating disturbances that may occur during the collection of sensor-based data. Finally, a comprehensive evaluation of performance and security has been carried out with various metrics. The findings indicate that the proposed solution effectively enhances the management of Internet of Medical Things data by providing improved privacy and security.

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【Keywords】blockchain; internet of medical things (IoMT); healthcare security; sensor registration; authentication; patient data monitoring

【发表时间】2024

【收录时间】2024-07-21

【文献类型】 实验仿真

【DOI】 10.1002/cpe.8213

A SYSTEMATIC ANALYSIS OF SUPPLY CHAIN RISK MANAGEMENT LIT-ERATURE: 2012-2021

【Author】 Xiao-Xin, Zhu Zhi-Min, Wen David, Regan Jiahui, Zhu

【影响因子】0.633

【主题类别】

区块链应用-实体经济-供应链

区块链治理-市场治理-风险管理

【Abstract】In order to secure supply chains (SCs), researchers and policy makers need to be abreast of developments in supply chain risk management (SCRM). This study selected frequently cited papers of WoS from the last 10 years, performing quantitative visualization analysis to establish the current trends within the field. Further attention was paid to those studies that focused on the impact of COVID-19. This study used a keyword timeline and clustering analysis map to establish the main research directions between 2012 to 2018, as well as the perspectives from which SC optimization was studied from 2018 to 2021. The key journals and research institutions for SCRM are established, as well as the key categories that the published literature falls under. Cluster analysis shows which areas in the published literature have the most references. Finally, the study establishes the direction of current trends within SCRM, as well as its understudied areas.

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【Keywords】Supply Chain; Risk Management; COVID-19; Literature Review; Quantitative Analysis

【发表时间】2024

【收录时间】2024-07-21

【文献类型】 综述

【DOI】 10.23055/ijietap.2024.31.3.9869

央行数字货币能带来货币国际化吗

【作者】 宋科; 孙翼; 朱斯迪

【作者单位】中国人民大学财政金融学院;中国财政金融政策研究中心、国际货币研究所;中国人民大学金融科技研究所;中国农业银行;对外经济贸易大学;中国人民大学国际货币研究所;

【文献来源】国际经济评论

【复合影响因子】4.860

【综合影响因子】2.830

【主题类别】

区块链治理-市场治理-数字货币

【摘要】当前,随着央行数字货币兴起和发展,其对货币国际化与国际货币体系变革的影响引发关注。货币国际化受经济、政治、文化以及军事等综合因素的影响,是一个长期滞后于经济金融全球化的“慢变量”。目前来看,货币数字化并不必然带来货币国际化,数字化不等于货币国际化。然而,在数字化时代,货币国际化一定需要货币数字化。央行数字货币有望给货币国际化带来至少以下三方面的边际改进:一是央行数字货币能够改进现行跨境支付方式,通过提高效率、降低成本以及规避制裁等方式推动跨境支付体系变革;二是央行数字货币的智能合约技术不仅能够拓展跨境支付场景,而且能通过预设触发条件缓解跨境使用央行数字货币的风险,提升央行数字货币的国际接受度;三是央行数字货币在便利性与匿名性方面相对更具优势,这有助于实现数字化时代隐私保护和支付效率之间的平衡,提高公众对于央行数字货币的接受程度。

【关键词】央行数字货币;;货币国际化;;跨境支付;;智能合约;;匿名性

【文献类型】 编辑社论

【DOI】

【发表时间】2024-07-21

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